# Best DataOps Platforms

  *By [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)*

   DataOps platforms act as command centers for DataOps. These solutions orchestrate people, processes, and technology to deliver a trusted data pipeline to their users. DataOps platforms assemble several types of data management software into an individual, integrated environment. Data flows in a simple manner from various data sources. These platforms are used to leverage any analytical tool—from data collection to data reporting via a single integrated platform. The platform unifies all the development and operations in data workflows. DataOps platforms are used to provide the flexibility to support a vast number of existing and new tools, as they are added. Organizations use the platform to control the entire workflow and related processes and ensure data-driven decisions are being made. Cycle times are reduced significantly and users are empowered with a single point of access to manage the data. Companies can leverage DataOps platforms to derive on-demand insights for successful business decisions.

DataOps platforms are primarily used by analytics and data teams within an organization; they are cross-functional and can be used across multiple verticals such as healthcare, finance, and others. IT operation teams can reduce storage infrastructure and increase staff productivity using a DataOps platform. Development and testing teams can decrease development cycles, app development times and reduce errors significantly by using this consolidated platform.

To qualify for inclusion in the DataOps category, a product must:

- Enable collaboration between data providers and data consumers to ensure data fluidity
- Combine different data management practices within a single platform, acting as an end-to-end solution
- Completely automate end-to-end data workflows across the data integration lifecycle
- Provide a dashboard and visualization tools to support data analysis and collaboration between various stakeholders
- Support deployment on any cloud environment





## Category Overview

**Total Products under this Category:** 99


## Trust & Credibility Stats

**Why You Can Trust G2's Software Rankings:**

- 30 Analysts and Data Experts
- 4,400+ Authentic Reviews
- 99+ Products
- Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.


## Best DataOps Platforms At A Glance

- **Leader:** [Databricks](https://www.g2.com/products/databricks/reviews)
- **Highest Performer:** [Boost.space](https://www.g2.com/products/boost-space/reviews)
- **Easiest to Use:** [5X](https://www.g2.com/products/5x/reviews)
- **Top Trending:** [Boost.space](https://www.g2.com/products/boost-space/reviews)
- **Best Free Software:** [Databricks](https://www.g2.com/products/databricks/reviews)


---

**Sponsored**

### QuerySurge

QuerySurge is an enterprise-grade data quality platform that leverages AI to continuously automate data validation across your entire ecosystem ‐ from data warehouses and big data lakes to BI reports and enterprise applications. With AI-powered test creation, scalable architecture, and the leading DevOps for Data CI/CD integration, QuerySurge ensures data integrity at every stage of the pipeline. Automated Data Validation Use Cases: QuerySurge provides a smart, AI-driven, data validation & ETL testing solution for your automated testing needs. - Data Warehouse / ETL Testing - DevOps for Data / Continuous Testing - Data Migration Testing - Business Intelligence (BI) Report Testing - Big Data Testing - Enterprise Application Data Testing What QuerySurge Provides: - Automation of your manual data validation and testing process - Ease-of-use, low-code/no-code features - Generative AI capabilities for test creation - Testing across 200+ data platforms - Integration into your CI/CD DataOps pipeline - Acceleration of your data analysis - Ensurance of regulatory compliance Key Features: - Data Connection Wizard provides an easy way to link to your data stores - Visual Query Wizard builds table-to-table and column-to-column tests without writing SQL - Generative AI module automatically creates transformation tests in bulk - DevOps for Data provides a RESTful API with 110+ calls and Swagger documentation and integrates into CI/CD pipelines - Create Custom Tests and modularize functions with snippets, set thresholds, stage data, check data types & duplicate rows, full text search, and asset tagging - Schedule tests to run immediately, at a predetermined date & time, or after any event from a build/release, CI/CD, DevOps, or test management solution - Multi-project support in a single instance, new Global Admin user, assign users and agents, import and export projects, and user activity log reports - Webhooks provide real-time integrations with DevOps, CI/CD, test management, and alerting tools - Ready-for-Analytics provides seamless integration with QuerySurge and your BI tool or open-source Metabase to create custom reports and dashboards and gain deeper, real-time insights into your data validation and ETL testing workflows - Data Analytics Dashboards and Data Intelligence Reports track, analyze, and communicate data quality



[Book a Demo](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list&secure%5Bcategory_id%5D=2686&secure%5Bdisplayable_resource_id%5D=2686&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=2686&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=54942&secure%5Bresource_id%5D=2686&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fdataops-platforms%3Fpage%3D7&secure%5Btoken%5D=fb1e0aaae697c762f4c6e3906800cd4bae94d74249f6aec2092ecc0c97aab09f&secure%5Burl%5D=https%3A%2F%2Fwww.querysurge.com%2Fget-started%2Fprivate-demo%3Futm_source%3DG2%26utm_medium%3Dcpc%26utm_campaign%3DG2-reviews&secure%5Burl_type%5D=book_demo)

---

## Top-Rated Products (Ranked by G2 Score)
  ### 1. [Databricks](https://www.g2.com/products/databricks/reviews)
  Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and over 60% of the Fortune 500 — rely on Databricks to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified Data Intelligence Platform that includes Agent Bricks, Lakeflow, Lakehouse, Lakebase and Unity Catalog.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 731

**User Satisfaction Scores:**

- **Data Observability:** 8.6/10 (Category avg: 8.9/10)
- **Testing capabilities:** 8.6/10 (Category avg: 8.6/10)
- **Ease of Use:** 8.9/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Databricks Inc.](https://www.g2.com/sellers/databricks-inc)
- **Company Website:** https://databricks.com
- **Year Founded:** 2013
- **HQ Location:** San Francisco, CA
- **Twitter:** @databricks (89,652 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/3477522/ (14,779 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer, Senior Data Engineer
  - **Top Industries:** Information Technology and Services, Financial Services
  - **Company Size:** 44% Enterprise, 40% Mid-Market


#### Pros & Cons

**Pros:**

- Features (288 reviews)
- Ease of Use (278 reviews)
- Integrations (189 reviews)
- Collaboration (150 reviews)
- Data Management (150 reviews)

**Cons:**

- Learning Curve (112 reviews)
- Expensive (97 reviews)
- Steep Learning Curve (96 reviews)
- Missing Features (69 reviews)
- Complexity (64 reviews)

  ### 2. [ServiceNow Workflow Data Fabric](https://www.g2.com/products/servicenow-workflow-data-fabric/reviews)
  Workflow Data Fabric is the AI‑ready data foundation of the ServiceNow AI Platform. It connects to any data—structured, unstructured, and streaming—contextualizes it with business meaning and governance, and controls it with lineage and policies so employees and AI agents can confidently act on real‑time information to prevent disruptions, resolve requests faster, and optimize operations—all on one platform. How Workflow Data Fabric turns data into instant action Connect Unify data from systems like Salesforce, SAP, Workday, data lakes, and event streams in real time without duplication or fragile point‑to‑point integrations. With Zero Copy Connectors, Stream Connect, External Content Connectors, and Integration Hub, WDF simplifies architecture and cuts integration cost and time. Contextualize Give data business meaning and make it trustworthy with an active Data Catalog, embedded governance, and lineage. Use Knowledge Graph to map relationships (e.g., customers, assets, orders) so AI agents and workflows understand context and make accurate decisions in the flow of work. Control Apply policies, permissions, and compliance guards across connected sources so the right people and AI agents access the right data, at the right time, with full auditability and traceability—no more shadow copies or opaque pipelines.


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 103

**User Satisfaction Scores:**

- **Data Observability:** 8.2/10 (Category avg: 8.9/10)
- **Testing capabilities:** 8.1/10 (Category avg: 8.6/10)
- **Ease of Use:** 8.0/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [ServiceNow](https://www.g2.com/sellers/servicenow)
- **Company Website:** https://www.servicenow.com/
- **Year Founded:** 2004
- **HQ Location:** Santa Clara, CA
- **Twitter:** @servicenow (54,113 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/29352/ (32,701 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Software Engineer
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 44% Enterprise, 30% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (37 reviews)
- Integrations (34 reviews)
- Automation (30 reviews)
- Efficiency Improvement (26 reviews)
- Data Management (25 reviews)

**Cons:**

- Complex Setup (23 reviews)
- Difficult Setup (17 reviews)
- Expensive (15 reviews)
- Slow Performance (14 reviews)
- Complexity (13 reviews)

  ### 3. [5X](https://www.g2.com/products/5x/reviews)
  5X is an end-to-end data and AI platform. The platform organizes your data regardless of source or format. Whether you have a dedicated data team or not, our platform
transforms fragmented data into actionable insights and apps. The customer feedback we get most often is, "This is self-explanatory," and "It's super easy to use." And that is exactly what our goal was—to create a powerful, all-in-one platform that's incredibly easy to use.  The modern data stack has evolved. It's no longer about stitching together vendors. The next-generation modern data stack is an all-in-one platform that offers speed, simplicity, and decreased cost of ownership. That's exactly what we have created at 5X. Companies use 5X for multiple reasons: 1) Speed & productivity. All-in-one data platforms are incredibly efficient. We've seen companies build use cases on day 1.  Contact us to see if you qualify for a free 48 hour jumpstart! 🚀 2) Decrease your total cost of ownership by 30% compared to building your own platform. This doesn't account the people hours needed to support a platform build 🤯 3) Use our full stack data consultancy for support on data engineering & analytics 👨‍💻 5X was founded in 2020 with presence in the USA, Singapore, UK and India. Our global team is 70+ people strong and rapidly growing. We’ve recently raised our seed round from Flybridge Capital and backed by top founders from companies like Datadog, Preset, Astronomer, Mode, Rudderstack and other prominent angel investors. For more information, visit 5X.co We don't just talk about speed and simplicity; we back it up with proof. Speak to us about our 48-hour jumpstart where we can build an end-to-end use case for you in 48 hours for free.


  **Average Rating:** 4.9/5.0
  **Total Reviews:** 81

**User Satisfaction Scores:**

- **Data Observability:** 9.1/10 (Category avg: 8.9/10)
- **Testing capabilities:** 9.0/10 (Category avg: 8.6/10)
- **Ease of Use:** 9.5/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 6.1/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [5X](https://www.g2.com/sellers/5x)
- **Company Website:** https://5x.co
- **Year Founded:** 2020
- **HQ Location:** San Francisco
- **Twitter:** @DataWith5x (49 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/datawith5x/ (128 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software, Financial Services
  - **Company Size:** 56% Mid-Market, 40% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (28 reviews)
- Customer Support (18 reviews)
- Features (14 reviews)
- Integrations (13 reviews)
- Data Integration (10 reviews)

**Cons:**

- Steep Learning Curve (5 reviews)
- Complex Setup (4 reviews)
- Feature Limitations (4 reviews)
- Learning Curve (4 reviews)
- Difficult Setup (3 reviews)

  ### 4. [dbt](https://www.g2.com/products/dbt/reviews)
  dbt is a transformation workflow that lets data teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines.


  **Average Rating:** 4.7/5.0
  **Total Reviews:** 199

**User Satisfaction Scores:**

- **Data Observability:** 8.7/10 (Category avg: 8.9/10)
- **Testing capabilities:** 8.9/10 (Category avg: 8.6/10)
- **Ease of Use:** 9.0/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Fivetran](https://www.g2.com/sellers/fivetran)
- **Year Founded:** 2012
- **HQ Location:** Oakland, CA
- **Twitter:** @fivetran (5,735 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/fivetran/ (1,738 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer, Analytics Engineer
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 57% Mid-Market, 28% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (38 reviews)
- Features (22 reviews)
- Automation (19 reviews)
- Transformation (17 reviews)
- Integrations (15 reviews)

**Cons:**

- Limited Functionality (14 reviews)
- Dependency Issues (12 reviews)
- Steep Learning Curve (10 reviews)
- Error Handling (9 reviews)
- Error Reporting (9 reviews)

  ### 5. [Boost.space](https://www.g2.com/products/boost-space/reviews)
  Boost.space is the #1 AI-Ready Data Sync platform on G2—recognized with over 100 customer-voted badges. ⭐️ Today's enterprises are investing heavily in AI, but most initiatives fail. Why? Because AI is "stateless"—it has no memory—and it's running on chaotic data fragmented across hundreds of applications. This data chaos costs companies an average of $15 million annually and wastes nearly 12 hours per employee every week.   Boost.space solves this foundational problem by creating a new category of enterprise infrastructure: the AI Memory Layer. We are not just another application; we are the persistent, unified memory that your entire AI and automation ecosystem needs to function intelligently. Our platform connects to over 2,400 apps to dismantle data silos, creating a single source of truth (SSOT) for all your business data. But unlike passive data warehouses, Boost.space is an active, read-write memory. Our real-time, three-way synchronization engine allows AI agents to not only read unified data but also act on it by writing changes back to your operational tools. At the heart of this is our Model Context Protocol (MCP), an "AI-Ready USB-C Port" for your enterprise that allows you to prompt your business in natural language. Whether you're building an AI-Ready PIM for e-commerce or an AI-Ready CDP for marketing, Boost.space provides the essential foundation, trusted by leaders like ŠKODA to make their data AI-ready.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 328

**User Satisfaction Scores:**

- **Data Observability:** 8.4/10 (Category avg: 8.9/10)
- **Testing capabilities:** 8.4/10 (Category avg: 8.6/10)
- **Ease of Use:** 7.3/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Boost.space s.r.o.](https://www.g2.com/sellers/boost-space-s-r-o)
- **Year Founded:** 2017
- **HQ Location:** Prague, CZ
- **Twitter:** @boostspace (81 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/boost-space/?originalSubdomain=cz (43 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** CEO, Founder
  - **Top Industries:** Marketing and Advertising, Consulting
  - **Company Size:** 99% Small-Business, 1% Mid-Market


#### Pros & Cons

**Pros:**

- Integrations (221 reviews)
- Automation (211 reviews)
- Easy Integrations (163 reviews)
- Features (150 reviews)
- Easy Integration (135 reviews)

**Cons:**

- Learning Curve (180 reviews)
- Steep Learning Curve (153 reviews)
- Learning Difficulty (65 reviews)
- Complex Setup (45 reviews)
- Beginner Difficulty (42 reviews)

  ### 6. [Flip](https://www.g2.com/products/kanerika-flip/reviews)
  FLIP by Kanerika is an AI-powered, low-code/no-code platform that automates enterprise workflows, streamlines data operations, and accelerates migrations — all without the need for technical expertise. It empowers teams to modernize faster, reduce manual effort, and focus on business outcomes. Key Capabilities: Automated Data Reconciliation Low-Code/No-Code DataOps Migration Accelerators AI Workforce Accounts Payable Automation FLIP helps organizations simplify data management, enhance accuracy, and accelerate digital transformation across industries.


  **Average Rating:** 5.0/5.0
  **Total Reviews:** 14

**User Satisfaction Scores:**

- **Data Observability:** 9.2/10 (Category avg: 8.9/10)
- **Testing capabilities:** 10.0/10 (Category avg: 8.6/10)
- **Ease of Use:** 10.0/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 3.3/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Kanerika](https://www.g2.com/sellers/kanerika)
- **Year Founded:** 2015
- **HQ Location:** Austin, US
- **LinkedIn® Page:** http://www.linkedin.com/company/kanerika (307 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Co-Founder
  - **Top Industries:** Computer Software
  - **Company Size:** 86% Small-Business, 21% Mid-Market


#### Pros & Cons

**Pros:**

- Features (10 reviews)
- Ease of Use (9 reviews)
- Fast Processing (7 reviews)
- Data Syncing (6 reviews)
- Customization (5 reviews)

**Cons:**

- Complex Setup (4 reviews)
- Expensive (4 reviews)
- Steep Learning Curve (4 reviews)
- Missing Features (3 reviews)
- Integration Issues (2 reviews)

  ### 7. [Monte Carlo](https://www.g2.com/products/monte-carlo/reviews)
  Monte Carlo, the data + AI observability leader, enables enterprise organizations to drive mission-critical initiatives with trusted foundations. Nasdaq, Honeywell, Roche, and hundreds of leading organizations depend on Monte Carlo's end-to-end platform to easily detect and resolve data + AI issues at scale. Offering thoughtfully automated workflows, intuitive collaboration tools and first-of-their-kind Observability Agents for monitoring and resolution, Monte Carlo extends it's powerful platform into every layer of the data + AI estate—data, system, code, and model—to help teams detect issues immediately, resolve them quickly, and scale coverage faster. Consistently ranked #1 in its category, Monte Carlo sets the industry standard for data + AI reliability, helping enterprise teams everywhere to reduce risk, accelerate innovation, and drive more value from their data + AI products.


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 498

**User Satisfaction Scores:**

- **Data Observability:** 9.2/10 (Category avg: 8.9/10)
- **Testing capabilities:** 7.7/10 (Category avg: 8.6/10)
- **Ease of Use:** 8.2/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Monte Carlo](https://www.g2.com/sellers/monte-carlo)
- **Company Website:** https://www.montecarlodata.com/
- **HQ Location:** San Francisco, US
- **Twitter:** @montecarlodata (1,576 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/monte-carlo-data/ (576 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer, Senior Data Engineer
  - **Top Industries:** Financial Services, Computer Software
  - **Company Size:** 49% Enterprise, 43% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (112 reviews)
- Alerts (107 reviews)
- Monitoring (97 reviews)
- Alerting System (78 reviews)
- Data Quality (53 reviews)

**Cons:**

- Alert Management (68 reviews)
- Alert Overload (62 reviews)
- Inefficient Alert System (53 reviews)
- UX Improvement (49 reviews)
- Limited Functionality (44 reviews)

  ### 8. [Peliqan](https://www.g2.com/products/peliqan/reviews)
  Peliqan.io is an all-in-one AI-first data integration and automation platform designed for business teams, scale-ups and consultants. Unlike traditional data tools that demand heavy engineering effort, Peliqan enables both business users and technical teams to connect, manage, and activate their data in one collaborative environment - without requiring a dedicated data engineer. With 250+ built-in connectors, Peliqan connects to databases, SaaS business applications (ERP, CRM, Accounting, HRM/ATS etc.), cloud storage, files and APIs as well as on-prem data sources. New connectors are available on demand within 5 business days. Peliqan offers one-click ELT pipelines to the built-in data warehouse, or you can bring your own data warehouse. Peliqan supports all major data warehouses. Thanks to Peliqan’s Excel add-in, business users and consultants can work with real-time data in Excel. Analysts and power users can use Peliqan’s advanced SQL editor with the support of an AI assistant to transform data and prepare business-ready data sets, which can be used in any BI tool such as Microsoft Power BI, Metabase, Tableau, Qlik, Looker etc. Users can also set up Reverse ETL flows. Developers can go even further with Peliqan’s low-code environment, with a built-in virtual AI Data Engineer, where they can: - Build & Publish interactive data apps - Automate writebacks into source systems - Publish API endpoints for data sharing - Implement custom pipelines - Build out internal AI Agents By empowering business users, analysts, consultants and developers, Peliqan dramatically reduces reliance on IT support and speeds up decision-making. Peliqan is not just an ELT data pipeline tool, it’s a complete solution for data orchestration, automation, and activation. Peliqan also acts as the data foundation for Agentic AI, ensuring that AI agents work with trusted, up-to-date 360° views of customers, products, orders, and more - at the speed of a cloud data warehouse. Peliqan’s data warehouse provides an AI-ready data layer out-of-the-box including: - Automatic vectorizing of structured and non-structured data for RAG (Retrieval-Augmented Generation) - Text-to-SQL - MCP Gateway In today’s landscape, a data warehouse is no longer just for BI - it’s the foundation for both BI and AI. With Peliqan.io, organizations can integrate, analyze, and activate their data seamlessly, empowering both humans and AI agents to make smarter, faster decisions.


  **Average Rating:** 4.8/5.0
  **Total Reviews:** 71

**User Satisfaction Scores:**

- **Data Observability:** 9.2/10 (Category avg: 8.9/10)
- **Testing capabilities:** 9.6/10 (Category avg: 8.6/10)
- **Ease of Use:** 9.3/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 4.9/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Peliqan](https://www.g2.com/sellers/peliqan)
- **Company Website:** https://peliqan.io
- **Year Founded:** 2022
- **HQ Location:** Gent
- **Twitter:** @Peliqan_io (8 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/peliqan-data (27 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software, Information Technology and Services
  - **Company Size:** 47% Mid-Market, 42% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (45 reviews)
- Integrations (43 reviews)
- Easy Integrations (37 reviews)
- Connectors (36 reviews)
- Data Management (36 reviews)

**Cons:**

- Learning Difficulty (18 reviews)
- Required Technical Skills (12 reviews)
- Feature Limitations (10 reviews)
- Learning Curve (10 reviews)
- Steep Learning Curve (9 reviews)

  ### 9. [Astro by Astronomer](https://www.g2.com/products/astro-by-astronomer/reviews)
  For data teams looking to increase the availability of trusted data, Astronomer provides Astro, the modern data orchestration platform, powered by Airflow. Astro enables data engineers, data scientists, and data analysts to build, run, and observe pipelines-as-code. Astronomer is the driving force behind Apache Airflow™, the de facto standard for expressing data flows as code. Airflow is downloaded more than 31 million times each month and is used by hundreds of thousands of teams around the world.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 135

**User Satisfaction Scores:**

- **Data Observability:** 8.2/10 (Category avg: 8.9/10)
- **Testing capabilities:** 8.0/10 (Category avg: 8.6/10)
- **Ease of Use:** 9.0/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Astronomer](https://www.g2.com/sellers/astronomer)
- **Company Website:** https://www.astronomer.io/
- **Year Founded:** 2018
- **HQ Location:** New York, US
- **Twitter:** @astronomerio (19,776 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/10019299 (4,630 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer, Senior Data Engineer
  - **Top Industries:** Information Technology and Services, Financial Services
  - **Company Size:** 47% Mid-Market, 38% Enterprise


#### Pros & Cons

**Pros:**

- Ease of Use (25 reviews)
- Efficiency Improvement (14 reviews)
- User Interface (13 reviews)
- Automation (11 reviews)
- Deployment Ease (10 reviews)

**Cons:**

- Expensive (8 reviews)
- Learning Difficulty (8 reviews)
- Learning Curve (6 reviews)
- Difficult Learning (5 reviews)
- Feature Limitations (5 reviews)

  ### 10. [Hightouch](https://www.g2.com/products/hightouch/reviews)
  Hightouch is the leading data and Agentic Marketing Platform for modern marketing teams. Trusted by brands like Domino’s, Autotrader, cars.com, Superhuman (formerly Grammarly), and PetSmart, Hightouch helps marketers deliver personalized experiences, optimize performance, and move faster with data and AI. With Hightouch, business users can drive revenue, grow brand awareness, and maximize ROI without relying on engineering. Hightouch’s Composable Customer Data Platform (CDP), named a Leader in the 2026 Gartner® Magic Quadrant™ for Customer Data Platforms, collects behavioral data, resolves identities into unified Customer 360 profiles, builds audiences, syncs to 300+ destinations (including leading ad platforms), and measures campaign impact—directly from your cloud data warehouse. On top of this foundation, Hightouch’s Agentic Marketing Platform uses your complete data and all of the context from your marketing and advertising tools to power true end-to-end lifecycle and performance marketing across paid and owned channels. Purpose-built agents help you go from analyzing campaign performance, to ideating new campaigns, to generating creative, to building segments and cross-channel journeys, to activating audiences and optimization signals back into your ad platforms and downstream tools—often in minutes instead of weeks. Hightouch is built for security, compliance, and scale. Your data stays in your environment—Hightouch never becomes a system of record—and the platform meets SOC 2 Type II, HIPAA, ISO-27001, GDPR, CCPA, and Privacy Shield standards, so even the most regulated organizations can confidently use customer data to power marketing. This approach gives global teams a single, trusted foundation for activation while preserving strong governance, clear audit trails, and regional data residency requirements.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 392

**User Satisfaction Scores:**

- **Data Observability:** 8.4/10 (Category avg: 8.9/10)
- **Testing capabilities:** 8.1/10 (Category avg: 8.6/10)
- **Ease of Use:** 9.2/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Hightouch](https://www.g2.com/sellers/hightouch)
- **Company Website:** https://hightouch.com/
- **Year Founded:** 2021
- **HQ Location:** San Francisco, US
- **Twitter:** @HightouchData (2,896 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/hightouchio/ (477 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer, Software Engineer
  - **Top Industries:** Computer Software, Information Technology and Services
  - **Company Size:** 63% Mid-Market, 25% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (16 reviews)
- Easy Integration (12 reviews)
- Customer Support (9 reviews)
- Easy Integrations (9 reviews)
- Easy Setup (9 reviews)

**Cons:**

- Expensive (5 reviews)
- Pricing Issues (5 reviews)
- Integration Issues (4 reviews)
- Slow Performance (4 reviews)
- Syncing Issues (4 reviews)

  ### 11. [Nexla](https://www.g2.com/products/nexla/reviews)
  Nexla is an enterprise-grade, AI-powered data integration platform designed to help organizations unlock data from any source and transform it into production-ready data products for AI and agents. With support for 550+ pre-built connectors and multiple integration styles, including ELT, ETL, streaming, APIs, and agentic RAG, the platform enables teams to build and manage data flows without writing code. Trusted by leading enterprises, Nexla processes over one trillion records per month across industries, ​​showcasing its ability to handle large volumes of data while maintaining performance and reliability. Innovators like Autodesk, DoorDash, Instacart, Johnson & Johnson, LinkedIn, and LiveRamp rely on Nexla to keep mission-critical data flowing seamlessly across their enterprises. Key features of Nexla include flexible deployment across cloud, hybrid, and on-premises environments, ensuring compliance with enterprise-grade security standards such as SOC 2 Type II, GDPR, CCPA, and HIPAA. Nexla delivers 10x faster implementation than traditional alternatives, turning data challenges and variety into competitive advantages. Try our AI Data Engineer at https://express.dev Increase the impact of your data engineering team with next-gen data integration: ✅ Eliminate costly replications & reduce storage bills ✅ Increase engineering productivity & capacity for innovation ✅ Empower users with Pro/Low/No-code collaboration ✅ Cut out maintenance with data validation, quality monitoring, & alerts ✅ Build production-ready custom GenAI applications Go beyond one traditional integration pattern, and invest in data architecture that supports: ✅ Any integration pattern (ELT, ETL, API / API proxy, & RAG - Retrieval Augmented Generation) ✅ Bi-directional connectors out of the box & on demand ✅ Any processing speed (streaming, real-time, batch) ✅ Unstructured, structured, or semi-structured data ✅ Complete data lineage search & tagging for governance ✅ Metadata-driven architecture for agility & scale Nexla is a Gartner Cool Vendor and pairs perfectly with the technologies you rely on: ✅ Compute: AWS, Azure, Google Cloud, On-Premise ✅ Storage: S3, Redshift, BigQuery, Snowflake, Oracle, Databricks, Kafka, Redis, MongoDB, Postgres, MySQL ✅ Applications: SAP, Salesforce, Marketo, Hubspot, Amazon Seller Central, Google Ads, API, Salesforce ✅ Catalogs: Alation, Collibra, data.world ✅ Webhooks, emails, FTP & APIs ✅ Vector database & LLM: Pinecone, GPT, Falcon, LLaMDa And many more Differentiators & Awards 🏆 2025 Highest Rating Gartner Peer Insights™ Voice of the Customer for Data Integration Tools 🏆 2024 Highest Rating Gartner Peer Insights™ Voice of the Customer for Data Integration Tools 🏆 2023 Highest Rating Gartner Peer Insights™ Voice of the Customer for Data Integration Tools 🏆 2022 Highest Rating Gartner Peer Insights™ Voice of the Customer for Data Integration Tools


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 63

**User Satisfaction Scores:**

- **Data Observability:** 8.9/10 (Category avg: 8.9/10)
- **Testing capabilities:** 8.7/10 (Category avg: 8.6/10)
- **Ease of Use:** 8.7/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 0/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Nexla](https://www.g2.com/sellers/nexla)
- **Company Website:** https://www.nexla.com/
- **Year Founded:** 2016
- **HQ Location:** San Mateo, California
- **Twitter:** @NexlaInc (947 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/nexla/ (76 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software, Insurance
  - **Company Size:** 41% Mid-Market, 33% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (21 reviews)
- Automation (14 reviews)
- Data Management (14 reviews)
- Integrations (13 reviews)
- Data Integration (10 reviews)

**Cons:**

- Learning Difficulty (7 reviews)
- Slow Performance (7 reviews)
- Difficult Learning (6 reviews)
- Learning Curve (6 reviews)
- Poor Documentation (6 reviews)

  ### 12. [ILUM](https://www.g2.com/products/ilum-ilum/reviews)
  Ilum: A Data Platform Built by Data Engineers, for Data Engineers Ilum is a Data Lakehouse platform that unifies data management, distributed processing, analytics, and AI workflows for AI engineers, data engineers, data scientists, and analysts. It belongs to the Data Platform, Data Lakehouse, and Data Engineering software categories and supports flexible deployment across cloud, on-premise, and hybrid environments. Ilum enables technical teams to build, operate, and scale modern data infrastructure using open standards. It integrates tools for batch processing, stream processing, notebook-based exploration, workflow orchestration, and business intelligence, All In a Single Platform. Ilum supports modern open table formats like Delta Lake, Apache Iceberg, Apache Hudi, and Apache Paimon. It also offers native integration with Apache Spark and Trino for compute, with Apache Flink support currently in development. Key features include: - SQL Editor: Query Delta, Iceberg, Hudi, or Spark SQL with autocomplete, result previews, and metadata inspection. - Data Lineage & Catalog: Visualize data flow using OpenLineage and explore datasets through a searchable Data Catalog. - Notebook Integration: Use built-in Jupyter notebooks pre-wired to Spark, metadata, and your data environment for exploration or modeling. - Spark Job Management: Submit, monitor, and debug Spark jobs with integrated logs, metrics, scheduling, and a built-in Spark History Server. - Trino Support: Run federated queries across multiple data sources using Trino directly from within Ilum. - Declarative Pipelines: Define repeatable ETL and analytics pipelines, with dependency tracking and recovery logic. - Automatic ERD Diagrams: Instantly generate ER diagrams from schemas to aid in data understanding and onboarding. - ML Experimentation & Tracking: Includes MLflow for managing experiments, tracking parameters, metrics, and artifacts, fully integrated with notebooks and data pipelines to streamline model development workflows. - AI Integration & Deployment: Supports both classical ML and modern AI use cases, including GenAI workflows, vector search, and embedding-based applications. Models can be registered, versioned, and deployed for inference within declarative pipelines. - Built-in AI Agent Interface: Ilum integrates, providing a GPT-style interface to interact with your data, trigger pipelines, generate SQL, or explore metadata using natural language, bringing GenAI capabilities directly into your data platform. - BI Dashboards: Native support for Apache Superset, with JDBC integration for Tableau, Power BI, and other BI tools. Additional highlights: - Multi-Cluster Management: Connect multiple Spark or Kubernetes clusters to scale and isolate workloads. - Fine-Grained Access Control: LDAP, OAuth2, and Hydra integration for secure, role-based access. - Hybrid Ready: Designed to replace Databricks or Cloudera in environments where cloud adoption is partial, regulated, or not possible.


  **Average Rating:** 4.9/5.0
  **Total Reviews:** 23

**User Satisfaction Scores:**

- **Data Observability:** 10.0/10 (Category avg: 8.9/10)
- **Testing capabilities:** 9.8/10 (Category avg: 8.6/10)
- **Ease of Use:** 9.3/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 7.5/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Ilum](https://www.g2.com/sellers/ilum)
- **Company Website:** https://ilum.cloud/
- **Year Founded:** 2019
- **HQ Location:** Santa Fe, US
- **Twitter:** @IlumCloud (19 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/ilum-cloud/ (4 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Telecommunications
  - **Company Size:** 52% Enterprise, 35% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (17 reviews)
- Features (17 reviews)
- Integrations (17 reviews)
- Setup Ease (16 reviews)
- Easy Integrations (15 reviews)

**Cons:**

- Complex Setup (9 reviews)
- Difficult Setup (9 reviews)
- Learning Curve (9 reviews)
- UX Improvement (8 reviews)
- Complexity (7 reviews)

  ### 13. [Y42](https://www.g2.com/products/y42-y42/reviews)
  Y42’s Turnkey Data Orchestration Platform with embedded Observability gives data practitioners a unified space to reliably build, monitor, and maintain the flow of data to power their business analytics and AI applications. Y42 provides native integration of best-of-breed open-source data tools, comprehensive data governance, and better collaboration for data teams. With Y42, organizations enjoy increased accessibility to data and can make data-driven decisions reliably and efficiently.


  **Average Rating:** 4.9/5.0
  **Total Reviews:** 21

**User Satisfaction Scores:**

- **Data Observability:** 9.2/10 (Category avg: 8.9/10)
- **Testing capabilities:** 9.6/10 (Category avg: 8.6/10)
- **Ease of Use:** 9.4/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Y42](https://www.g2.com/sellers/y42-f0288f79-5826-460d-ba84-59d0f8b2f3b3)
- **Year Founded:** 2020
- **HQ Location:** Berlin, DE
- **Twitter:** @y42dotcom (279 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/64543299 (23 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 52% Small-Business, 38% Mid-Market


  ### 14. [IBM StreamSets](https://www.g2.com/products/ibm-streamsets/reviews)
  IBM StreamSets is a robust streaming data integration tool for hybrid, multi-cloud environments that enables real-time decision making. It allows ingestion and in-flight transformation of structured, unstructured, and semi-structured data from streaming sources, and reliably delivers trusted data into diverse destinations. Flexible deployment options promote security, cost-effectiveness and performance. With several pre-built connectors, an intuitive no-code/low-code interface, and automatic adaptability to data drifts, StreamSets accelerates data pipeline operationalization. It integrates with IBM’s broader data integration capabilities, enabling reliable pipelines that unify multiple data integration patterns, underpinned by data observability capabilities for continuous data quality monitoring and remediation. That’s why the largest companies in the world trust StreamSets to power millions of data pipelines for modern analytics, data science, smart applications, and hybrid integration.


  **Average Rating:** 4.0/5.0
  **Total Reviews:** 115

**User Satisfaction Scores:**

- **Data Observability:** 6.7/10 (Category avg: 8.9/10)
- **Testing capabilities:** 7.1/10 (Category avg: 8.6/10)
- **Ease of Use:** 8.4/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Year Founded:** 1911
- **HQ Location:** Armonk, NY
- **Twitter:** @IBM (709,023 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (324,553 employees on LinkedIn®)
- **Ownership:** SWX:IBM

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer, Software Engineer
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 42% Enterprise, 33% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (30 reviews)
- User Interface (16 reviews)
- Data Management (15 reviews)
- Data Pipelining (15 reviews)
- Integrations (14 reviews)

**Cons:**

- Learning Curve (13 reviews)
- Expensive (10 reviews)
- Learning Difficulty (8 reviews)
- Slow Performance (8 reviews)
- Steep Learning Curve (8 reviews)

  ### 15. [Stonebranch](https://www.g2.com/products/stonebranch/reviews)
  The Stonebranch Workload Automation solution, part of our Universal Automation Center platform, helps organizations automate, manage, and orchestrate their IT processes - across hybrid IT environments. 1. Workflow Orchestration and Automation: Holistically control scripts, jobs, tasks, and IT processes running across your on-prem, hybrid cloud, and/or multi-cloud environments. 2. Real-Time Automation: With our event-driven automation technology, it is now possible to achieve real-time automation across your entire hybrid IT environment. 3. Self-Service Automation: With a focus on ease-of-use, you can empower your workforce with self-service automation using member roles and permissions. 4. BI & Analytics: Centralize operational control and insight with proactive monitoring, reporting, and alerts. Product Features: - Drag-and-drop Workflow Creation: You don’t have to be a developer to create automation. Custom scripting is a thing of the past. Easily create workflows with an intuitive drag-and-drop user interface. - DevOps enabled: Align priorities between IT Ops and DevOps with Jobs-as-Code, Infrastructure-as-Code, and bundle-and-promote features. - Limitless 3rd Party Integrations: Integrate into any platform or application from the mainframe to the cloud. Use pre-packaged integrations, build your own, or download integration blueprints from the community-driven opensource marketplace. - Available on-premises or as a SaaS-based deployment, the UAC is a modern platform built to scale with your business.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 123

**User Satisfaction Scores:**

- **Data Observability:** 9.2/10 (Category avg: 8.9/10)
- **Testing capabilities:** 8.9/10 (Category avg: 8.6/10)
- **Ease of Use:** 8.7/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Stonebranch, Inc](https://www.g2.com/sellers/stonebranch-inc)
- **Company Website:** https://www.stonebranch.com
- **Year Founded:** 1999
- **HQ Location:** Alpharetta, GA
- **Twitter:** @Stonebranch (1,176 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/71261/ (173 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Software Engineer
  - **Top Industries:** Information Technology and Services, Insurance
  - **Company Size:** 54% Enterprise, 31% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (22 reviews)
- Automation (15 reviews)
- Customer Support (11 reviews)
- Workflow Automation (9 reviews)
- Easy Integrations (8 reviews)

**Cons:**

- Complexity (15 reviews)
- Difficult Learning (8 reviews)
- Poor Documentation (8 reviews)
- Learning Curve (6 reviews)
- Difficulty (4 reviews)

  ### 16. [Keboola](https://www.g2.com/products/keboola/reviews)
  Keboola is the unified AI & Data orchestration platform that empowers organizations to turn data into business value faster and more securely than ever. It acts as your agentic AI co-pilot for data workflows, automating everything from integration to insight. With Keboola, Engineering teams, digital natives, startup CTOs, and innovation leads alike can rapidly build and manage data products, applications, AI agents, and autonomous crews seamlessly—without sacrificing compliance or security. Built for Every Data Persona: Whether you’re a seasoned data engineer or a business analyst, Keboola is built to make you successful. Data engineers love the open extensibility – code in SQL, Python, R, or use our API/CLI to tailor any step. Analysts and non-coders love the self-service UI – point-and-click data pipeline assembly, drag-and-drop transformations with text to SQL on semantic layer, and one-click deployment of pre-built workflows. Collaboration is seamless, with shared workspaces and sandboxes that let teams build and share data products freely without affecting production. What sets us apart? With Keboola, you can build and manage data products, applications, AI agents, and autonomous crews seamlessly—without sacrificing compliance or security. 🔗 Unified Connectivity: Effortlessly connect to 700+ data sources (databases, SaaS apps, and APIs) .Real-time Streams, Change Data Capture or batch. 🤖 Agentic AI Orchestration: Keboola’s AI-driven engine orchestrates data pipelines and ML workflows automatically. It can trigger the next steps based on data events or quality checks, and dynamically allocate resources. Think of it as an autopilot for your data & AI, ensuring pipelines run optimally and recover on their own from hiccups. 🛡️ Built-in Governance & Security: Every dataset and process in Keboola is governed. Fine-grained access controls, lineage tracking, and audit logs are native to the platform. Compliance is simplified – SOC 2, GDPR, and industry standards are supported out-of-the-box. 🚀 Rapid Development & Prototyping: Innovate without constraints. Spin up isolated dev/test sandboxes in seconds to prototype new data products or AI models. 🌎 Multi-Cloud Scalability: Built on a cloud-native architecture, Keboola scales with your needs. Deploy on your preferred cloud (AWS, Azure, GCP) and let Keboola handle the heavy lifting – elastic compute, parallel processing, and workload optimization. Start small and scale to enterprise workloads globally, without re-architecting. 💡 End-to-End Insight Activation: Because Keboola unifies your data pipelines, analytics, and ML, you can go from raw data to AI-driven insights in record time. Why Keboola: Instead of cobbling together multiple tools for integration, ETL/ELT, data catalogs, automation, and AI, Keboola delivers a single platform that does it all – with unprecedented ease and intelligence. Our customers have replaced 5-10 disparate tools with Keboola’s unified solution, drastically accelerating delivery. Join 30,000+ companies and industry leaders who use Keboola to supercharge their data teams. Whether you need to deliver data to AI Agents, streamline a complex data estate, or build and share data products to business, Keboola’s AI orchestration platform adapts to your needs – freeing you to focus on innovation and business growth.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 134

**User Satisfaction Scores:**

- **Data Observability:** 8.4/10 (Category avg: 8.9/10)
- **Testing capabilities:** 7.7/10 (Category avg: 8.6/10)
- **Ease of Use:** 8.6/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Keboola](https://www.g2.com/sellers/keboola)
- **Company Website:** https://www.keboola.com
- **Year Founded:** 2008
- **HQ Location:** Prague
- **Twitter:** @keboola (2,007 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/keboola/ (113 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Analyst, Data Engineer
  - **Top Industries:** Information Technology and Services, Marketing and Advertising
  - **Company Size:** 64% Mid-Market, 21% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (35 reviews)
- Features (27 reviews)
- Data Management (26 reviews)
- Integrations (26 reviews)
- Customer Support (25 reviews)

**Cons:**

- Learning Curve (14 reviews)
- Complexity (13 reviews)
- Steep Learning Curve (11 reviews)
- Data Management (9 reviews)
- UX Improvement (9 reviews)

  ### 17. [Atlan](https://www.g2.com/products/atlan/reviews)
  Atlan is the context layer for enterprise AI. It continuously reads your warehouses, databases, pipelines, BI tools, and business systems to reverse construct an enterprise data graph that captures assets, lineage, entities, metrics, policies, and relationships. On top of that graph, it enriches and curates machine-readable semantics — descriptions, popular joins, KPI and metric definitions, ontologies, and business rules — and organizes them into governed, versioned context repos: bounded bundles of context that reflect how your company defines key concepts and makes decisions. These context repos are then exposed through open interfaces (SQL, APIs, SDKs, OSI/MCP-style protocols) so that agents, copilots, and AI applications can call the same trusted context in real time, rather than each team hard-coding its own logic. Human-on-the-loop governance workflows for conflict resolution, deprecation, feedback, and certification keep that context trustworthy as the business, data, and models evolve.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 124

**User Satisfaction Scores:**

- **Data Observability:** 8.5/10 (Category avg: 8.9/10)
- **Testing capabilities:** 7.4/10 (Category avg: 8.6/10)
- **Ease of Use:** 9.0/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Atlan](https://www.g2.com/sellers/atlan)
- **Company Website:** https://www.atlan.com
- **Year Founded:** 2019
- **HQ Location:** New York, US
- **Twitter:** @AtlanHQ (9,720 Twitter followers)
- **LinkedIn® Page:** https://in.linkedin.com/company/atlan-hq (580 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Financial Services, Computer Software
  - **Company Size:** 53% Mid-Market, 40% Enterprise


#### Pros & Cons

**Pros:**

- Ease of Use (18 reviews)
- User Interface (12 reviews)
- Features (11 reviews)
- Data Lineage (10 reviews)
- Easy Setup (10 reviews)

**Cons:**

- Learning Curve (5 reviews)
- Limited Functionality (5 reviews)
- User Interface Issues (5 reviews)
- Difficult Learning (4 reviews)
- Integration Issues (4 reviews)

  ### 18. [QuerySurge](https://www.g2.com/products/querysurge/reviews)
  QuerySurge is an enterprise-grade data quality platform that leverages AI to continuously automate data validation across your entire ecosystem ‐ from data warehouses and big data lakes to BI reports and enterprise applications. With AI-powered test creation, scalable architecture, and the leading DevOps for Data CI/CD integration, QuerySurge ensures data integrity at every stage of the pipeline. Automated Data Validation Use Cases: QuerySurge provides a smart, AI-driven, data validation & ETL testing solution for your automated testing needs. - Data Warehouse / ETL Testing - DevOps for Data / Continuous Testing - Data Migration Testing - Business Intelligence (BI) Report Testing - Big Data Testing - Enterprise Application Data Testing What QuerySurge Provides: - Automation of your manual data validation and testing process - Ease-of-use, low-code/no-code features - Generative AI capabilities for test creation - Testing across 200+ data platforms - Integration into your CI/CD DataOps pipeline - Acceleration of your data analysis - Ensurance of regulatory compliance Key Features: - Data Connection Wizard provides an easy way to link to your data stores - Visual Query Wizard builds table-to-table and column-to-column tests without writing SQL - Generative AI module automatically creates transformation tests in bulk - DevOps for Data provides a RESTful API with 110+ calls and Swagger documentation and integrates into CI/CD pipelines - Create Custom Tests and modularize functions with snippets, set thresholds, stage data, check data types & duplicate rows, full text search, and asset tagging - Schedule tests to run immediately, at a predetermined date & time, or after any event from a build/release, CI/CD, DevOps, or test management solution - Multi-project support in a single instance, new Global Admin user, assign users and agents, import and export projects, and user activity log reports - Webhooks provide real-time integrations with DevOps, CI/CD, test management, and alerting tools - Ready-for-Analytics provides seamless integration with QuerySurge and your BI tool or open-source Metabase to create custom reports and dashboards and gain deeper, real-time insights into your data validation and ETL testing workflows - Data Analytics Dashboards and Data Intelligence Reports track, analyze, and communicate data quality


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 30

**User Satisfaction Scores:**

- **Data Observability:** 8.8/10 (Category avg: 8.9/10)
- **Testing capabilities:** 9.1/10 (Category avg: 8.6/10)
- **Ease of Use:** 8.7/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 5.8/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [QuerySurge](https://www.g2.com/sellers/querysurge)
- **Company Website:** https://www.querysurge.com
- **Year Founded:** 2012
- **HQ Location:** New York, US
- **Twitter:** @QuerySurge (6,449 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/querysurge/ (7 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services
  - **Company Size:** 39% Enterprise, 26% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (17 reviews)
- Features (12 reviews)
- Automation (8 reviews)
- Capabilities (8 reviews)
- Easy Setup (8 reviews)

**Cons:**

- Limited Functionality (5 reviews)
- Missing Features (5 reviews)
- Inaccuracy Issues (4 reviews)
- Slow Performance (4 reviews)
- Complex Setup (3 reviews)

  ### 19. [Mozart Data](https://www.g2.com/products/mozart-data-mozart-data/reviews)
  Backed by award-winning data analyst support, Mozart Data is the fastest way to set up scalable, reliable data infrastructure that doesn’t need to be maintained by you. Mozart Data’s all-in-one modern data platform empowers anyone to easily centralize, organize, and analyze their data without engineering resources. Instead of piecing together multiple tools, companies get everything they need to spin up a data stack in an hour — ETL, a data warehouse, and a data transformation tool — and gain visibility into their data pipelines. Join other data-driven companies, like Zeplin, Rippling, Modern Treasury, and Tempo, that are already getting the most out of their data. Learn more at https://www.mozartdata.com


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 68

**User Satisfaction Scores:**

- **Data Observability:** 8.7/10 (Category avg: 8.9/10)
- **Testing capabilities:** 8.0/10 (Category avg: 8.6/10)
- **Ease of Use:** 9.3/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Mozart Data](https://www.g2.com/sellers/mozart-data)
- **Year Founded:** 2020
- **HQ Location:** San Francisco, US
- **Twitter:** @MozartData (449 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/mozartdata/ (16 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software, Financial Services
  - **Company Size:** 53% Small-Business, 47% Mid-Market


  ### 20. [Weld](https://www.g2.com/products/weld-weld/reviews)
  Weld delivers an ultra-fast, secure, and reliable way to move data from all your tools, applications, and databases into cloud data warehouses, such as Snowflake, BigQuery, and Databricks. Deploy data pipelines in minutes with connectors that adapt to schema changes, detect duplicates, self-heal on failure, and run without maintenance, so your data team can focus on insights, not infrastructure.


  **Average Rating:** 4.8/5.0
  **Total Reviews:** 101

**User Satisfaction Scores:**

- **Data Observability:** 8.0/10 (Category avg: 8.9/10)
- **Testing capabilities:** 7.6/10 (Category avg: 8.6/10)
- **Ease of Use:** 8.8/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 5.5/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Weld](https://www.g2.com/sellers/weld-733aad41-2e36-4f42-9349-7d847f41d873)
- **Year Founded:** 2021
- **HQ Location:** Copenhagen, DK
- **Twitter:** @WeldHQ (98 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/weldhq/ (97 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** CEO
  - **Top Industries:** Computer Software, Retail
  - **Company Size:** 58% Small-Business, 41% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (16 reviews)
- Customer Support (13 reviews)
- Features (12 reviews)
- Automation (11 reviews)
- Data Integration (9 reviews)

**Cons:**

- Limited Connectors (8 reviews)
- Feature Limitations (6 reviews)
- Missing Features (5 reviews)
- Limited Integrations (4 reviews)
- Connectivity Issues (3 reviews)

  ### 21. [Acceldata](https://www.g2.com/products/acceldata/reviews)
  Acceldata is a pioneering provider of enterprise solutions in data observability and Agentic Data Management. Its technology enables organizations to monitor, manage, and improve the reliability, quality, and performance of data systems across cloud, hybrid, and on-prem environments. Building on its foundation in data observability, Acceldata developed an Agentic Data Management platform that applies AI agents to autonomously detect, analyze, and resolve issues across the data lifecycle. This approach brings together observability, governance, and optimization into a unified system, allowing data environments to self-monitor, self-heal, and adapt over time. By moving from manual, reactive operations to more intelligent, automated processes, Acceldata supports scalable, efficient, and context-aware data management across the enterprise. Core Features of Acceldata’s Agentic Data Management Platform 1. Autonomous AI Agents: Acceldata deploys over 10 specialized AI agents designed to manage core data functions such as data quality, lineage, profiling, governance, pipeline health, and cost optimization. These agents continuously scan systems, detect issues, reason about their cause, and either take direct action or escalate with human oversight. They collaborate to improve data reliability, reduce downtime, and drive informed decision-making. 2. xLake Reasoning Engine: At the core of the platform is the xLake Reasoning Engine—a high-scale, AI-aware engine built to handle exabytes of data. It executes across hybrid and multi-cloud environments, translating business rules into intelligent data actions. xLake enables context-aware processing and powers the agents’ ability to reason across telemetry, metadata, and historical trends. 3. Contextual Memory and Learning: Agents don’t operate in isolation. They remember past patterns, recall prior actions, and improve over time using contextual memory. This learning ability allows agents to adapt policies, refine thresholds, and prevent repeat incidents, making pipelines and systems progressively smarter and more resilient. 4. Natural Language Interface – The Business Notebook: Acceldata features a conversational interface called the Business Notebook. This AI-powered workspace allows business users and technical teams to interact with data in natural language. It explains agent actions, visualizes lineage, and empowers non-technical users to ask questions, make decisions, and access insights without needing SQL or scripting knowledge. 5. Real-Time Data Observability and Self-Healing: The platform goes beyond traditional monitoring by offering agentic observability. It autonomously scans data systems for anomalies, schema drift, freshness decay, and operational failures. Once detected, agents not only alert but also remediate issues in real time—ensuring continuous data reliability and pipeline health. 6. Policy-Driven Governance and Compliance: Acceldata embeds governance into the fabric of your data workflows. With policy agents, organizations can define and enforce access controls, data protection rules, audit logging, and compliance policies like GDPR, HIPAA, and BCBS 239—all without manual configuration. These policies evolve automatically using machine learning and agent feedback loops. 7. Unified Data Discovery and Classification: The Discovery engine continuously scans across cloud platforms, data lakes, and warehouses to classify, tag, and map data assets. It auto-generates lineage maps, enriches assets with context (e.g., usage, sensitivity), and supports plain-language search. This eliminates the need for separate data catalogs and makes every dataset AI-ready. 8. Agent Studio for Custom Agent Creation: With Agent Studio, organizations can build and deploy their own AI agents tailored to their business needs. Whether it’s a vertical-specific data rule, a proprietary policy, or a unique remediation workflow, Agent Studio offers the flexibility to extend the platform’s capabilities and orchestrate multi-agent workflows.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 53

**User Satisfaction Scores:**

- **Data Observability:** 9.5/10 (Category avg: 8.9/10)
- **Testing capabilities:** 7.6/10 (Category avg: 8.6/10)
- **Ease of Use:** 8.5/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Acceldata](https://www.g2.com/sellers/acceldata)
- **Company Website:** https://www.acceldata.io/
- **Year Founded:** 2018
- **HQ Location:** Campbell, CA
- **Twitter:** @acceldataio (340 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/acceldata (271 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software, Information Technology and Services
  - **Company Size:** 61% Enterprise, 22% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (18 reviews)
- Customer Support (15 reviews)
- Efficiency Improvement (13 reviews)
- Features (13 reviews)
- Monitoring (13 reviews)

**Cons:**

- UX Improvement (9 reviews)
- Complex Setup (6 reviews)
- Difficult Setup (6 reviews)
- Learning Curve (6 reviews)
- Learning Difficulty (6 reviews)

  ### 22. [Witboost](https://www.g2.com/products/witboost/reviews)
  Witboost is a pioneering platform that simplifies data product lifecycle management through automated governance and business-driven data discovery. It is designed to help organizations manage their data initiatives efficiently, ensuring compliance, strategic alignment, and collaboration. The platform enables scalable and secure data operations across diverse technology stacks, all while avoiding vendor lock-in, making it a versatile solution for modern data challenges. Targeted at data teams, platform engineers, business analysts, and IT leaders, Witboost delivers a unified experience by integrating business context, governance automation, and IT delivery workflows. This integration streamlines data product development, accelerates time-to-market, and embeds compliance into processes, significantly reducing the risks associated with traditional manual governance practices. As organizations increasingly rely on data-driven decision-making, Witboost provides the necessary tools to facilitate this transition smoothly, ensuring that data initiatives align with business objectives. A standout feature of Witboost is its computational governance engine, which empowers organizations to shift compliance left in the development process. Governance is enforced automatically through policies and guardrails that validate architecture, metadata, quality, and operational standards during both build time and runtime. This proactive approach ensures that every data product is technically robust and compliant by design, minimizing the likelihood of issues arising post-deployment. By embedding governance into the development lifecycle, Witboost helps organizations maintain high standards while fostering innovation. Central to the platform are data contracts, which allow teams to define, version, validate, and monitor agreements covering schema definitions, service level agreements (SLAs), semantics, and quality thresholds. These contracts are seamlessly integrated into change management flows, fostering trust between data producers and consumers while minimizing data friction across the enterprise. This feature enhances collaboration and ensures that all stakeholders are aligned on data expectations, ultimately leading to more effective data utilization. Witboost also offers customizable blueprints and templates that enable platform teams to define reusable golden paths. These resources guide data teams through compliant implementations, reducing cognitive load and promoting standardization without sacrificing autonomy. Additionally, the platform features a curated, business-friendly data marketplace that streamlines discovery and access. Governed and contract-bound data products are presented in a clean, searchable interface, allowing for fast, self-service access without the need for tickets or excessive friction. With the embedded AI assistant, Witty, users benefit from metadata curation and design validation, further increasing adoption and consistency while reducing manual effort. Witboost's technology-agnostic, extensible, and future-proof design also supports large organizations in scaling their data mesh initiatives with speed, safety, and real impact.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 19

**User Satisfaction Scores:**

- **Data Observability:** 10.0/10 (Category avg: 8.9/10)
- **Ease of Use:** 8.1/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Agile Lab](https://www.g2.com/sellers/agile-lab)
- **Company Website:** https://www.agilelab.it
- **Year Founded:** 2013
- **HQ Location:** Torino
- **LinkedIn® Page:** https://www.linkedin.com/company/agile-lab/ (293 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 74% Enterprise, 16% Mid-Market


#### Pros & Cons

**Pros:**

- Data Discovery (5 reviews)
- Flexibility (5 reviews)
- Learning (3 reviews)
- Accessibility (2 reviews)
- Centralized Management (2 reviews)

**Cons:**

- Limited Customization (2 reviews)
- Complexity (1 reviews)
- Complex Setup (1 reviews)
- Difficult Learning (1 reviews)
- Inadequate Reporting (1 reviews)

  ### 23. [Coalesce Catalog (formerly CastorDoc)](https://www.g2.com/products/castor-doc/reviews)
  Coalesce Catalog is a collaborative, automated data discovery & catalog tool. We believe that data people spend way too much time trying to find and understand their data. Coalesce Catalog redesigns how data people collaborate. It provides a single source of truth to reference and document all the knowledge related to data within your company. If you are looking for a table related to your customers, just look for it as you would in Google, and Coalesce Catalog provides you with all the context you will need for your analysis. Inspired by internal tools developed by Uber, Airbnb, Lyft, and Spotify, Coalesce Catalog has developed a plug-and-play solution that deploys in minutes to drive value for companies of all sizes. Discover and catalog your data today with Coalesce Catalog.


  **Average Rating:** 4.7/5.0
  **Total Reviews:** 63

**User Satisfaction Scores:**

- **Data Observability:** 8.5/10 (Category avg: 8.9/10)
- **Testing capabilities:** 8.1/10 (Category avg: 8.6/10)
- **Ease of Use:** 9.6/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Coalesce](https://www.g2.com/sellers/coalesce)
- **Company Website:** https://coalesce.io/
- **Year Founded:** 2020
- **HQ Location:** San Francisco, CA
- **LinkedIn® Page:** https://www.linkedin.com/company/coalesceio/ (127 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services, Financial Services
  - **Company Size:** 59% Mid-Market, 27% Enterprise


#### Pros & Cons

**Pros:**

- Ease of Use (3 reviews)
- Collaboration (2 reviews)
- Connectivity (2 reviews)
- Data Lineage (2 reviews)
- Useful (2 reviews)

**Cons:**

- Connector Issues (1 reviews)
- Integration Issues (1 reviews)
- Limitations (1 reviews)

  ### 24. [Datafold](https://www.g2.com/products/datafold/reviews)
  Datafold is a data observability platform that helps companies prevent data catastrophes. It has a unique ability to identify, prioritize and investigate data quality issues proactively before they affect production. Datafold’s proactive approach to data quality helps data teams gain visibility and confidence in the quality of their analytical data through data profiling, column-level lineage and intelligent anomaly detection. Datafold also helps automate regression testing of ETL code with its Data Diff feature that instantly shows how a change in ETL or BI code affects the produced data, both on a statistical level and down to individual rows and values. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 24

**User Satisfaction Scores:**

- **Data Observability:** 8.2/10 (Category avg: 8.9/10)
- **Testing capabilities:** 9.3/10 (Category avg: 8.6/10)
- **Ease of Use:** 8.8/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Datafold](https://www.g2.com/sellers/datafold)
- **Year Founded:** 2020
- **HQ Location:** New York, US
- **Twitter:** @datafoldcom (1,109 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/datafold/ (33 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services
  - **Company Size:** 54% Mid-Market, 29% Small-Business


  ### 25. [Datacoves](https://www.g2.com/products/datacoves/reviews)
  Datacoves is an enterprise DataOps platform with managed dbt Core and Airflow for data transformation and orchestration. We offer VS Code in the browser for dbt development with the ability to include preferred VS Code extensions and Python libraries such as the official Snowflake Extension and Snowpark. You may also optionally use our managed Airbyte and Superset for a full end-to-end solution.


  **Average Rating:** 4.7/5.0
  **Total Reviews:** 17

**User Satisfaction Scores:**

- **Data Observability:** 8.9/10 (Category avg: 8.9/10)
- **Testing capabilities:** 9.3/10 (Category avg: 8.6/10)
- **Ease of Use:** 8.9/10 (Category avg: 9.0/10)
- **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10)


**Seller Details:**

- **Seller:** [Datacoves Inc](https://www.g2.com/sellers/datacoves-inc)
- **Year Founded:** 2021
- **HQ Location:** Thousand Oaks, California
- **Twitter:** @datacoves (478 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/datacoves/ (13 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 47% Enterprise, 29% Small-Business


#### Pros & Cons

**Pros:**

- API Integration (1 reviews)
- Continuous Improvement (1 reviews)
- Customer Support (1 reviews)
- Dashboards (1 reviews)
- Data Centralization (1 reviews)

**Cons:**

- Alert Overload (1 reviews)
- Dashboard Issues (1 reviews)
- Integration Issues (1 reviews)
- Lack of Information (1 reviews)
- Limited Visualization (1 reviews)



## Parent Category

[IT Infrastructure Software](https://www.g2.com/categories/it-infrastructure)



## Related Categories

- [Data Quality Tools](https://www.g2.com/categories/data-quality)
- [ETL Tools](https://www.g2.com/categories/etl-tools)
- [Data Observability Software](https://www.g2.com/categories/data-observability)