# Best Data Observability Software - Page 3 *By [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)* Data observability involves the complete monitoring, managing, and understanding of the modern data tech stack. These tools allow companies to better manage their data by helping them discover and solve real-time data issues and gain complete insight into the system’s data health. Data observability tools help companies accelerate the adoption of data across departments. This helps in making strategic and data-driven decisions that benefit the entire organization. The concept of data observability stems from best practices learned from DevOps software to manage impartial, inaccurate, or erroneous data. These best practices, which include optimizing logs, real-time insights, and so on, enable the creation of error-free and trusted data across the entire data stack, which includes data sources, data warehouses, ETL tools, ML/BI tools, etc. Data observability tools are a part of [DataOps platforms](https://www.g2.com/categories/dataops-platforms). DataOps platforms assemble several types of data management software into an individual, integrated environment. The platform unifies all the development and operations in data workflows. Data observability software focuses on monitoring the health of the data pipelines and the overall system. Data observability tools differ from [monitoring software](https://www.g2.com/categories/monitoring) since the latter focuses on pre-determined metrics to identify bugs, whereas data observability focuses on real-time detection and resolution. Data observability also differs from [data quality software](https://www.g2.com/categories/data-quality), wherein the former focuses on reducing the number of data incidents while accelerating resolution time. Data quality is the result of powerful data observability across the modern data stack. To qualify for inclusion in the Data Observability category, a product must: - Proactively monitor, alert, track, log, compare, and analyze data for any errors or issues across the entire data stack - Monitor data at rest and data in motion, and does not require data extraction from current storage location - Connect to an existing stack without any need to write code or modify data pipelines ## Category Overview **Total Products under this Category:** 60 ## Trust & Credibility Stats **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 2,300+ Authentic Reviews - 60+ 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 Data Observability Software At A Glance - **Leader:** [Monte Carlo](https://www.g2.com/products/monte-carlo/reviews) - **Highest Performer:** [SquaredUp](https://www.g2.com/products/squaredup-squaredup/reviews) - **Easiest to Use:** [Dash0](https://www.g2.com/products/dash0/reviews) - **Top Trending:** [Sifflet](https://www.g2.com/products/sifflet/reviews) - **Best Free Software:** [Metaplane](https://www.g2.com/products/metaplane/reviews) ## Top-Rated Products (Ranked by G2 Score) ### 1. [Fluency Platform](https://www.g2.com/products/fluency-platform/reviews) Ingext is a data fabric platform that helps enterprises collect, process, and route high-volume telemetry and observability data across diverse environments in real time. Designed for scalability and cost efficiency, Ingext simplifies the movement of data between sources, storage, and analytics systems, enabling organizations to control costs while maintaining full visibility into their operations. Unlike traditional data pipelines or point-to-point integrations, Ingext provides a unified layer that sits between data producers (such as cloud services, security tools, and infrastructure logs) and data consumers (such as SIEMs, data lakes, or analytics platforms). Its architecture allows teams to normalize, enrich, filter, and transform data streams before they reach expensive downstream systems—reducing storage overhead and improving the quality of analytics. Ingext supports cloud, hybrid, and on-premises deployments, giving organizations granular control over how and where data is processed. It’s designed for IT, security, and operations teams who need consistent, policy-driven data handling without vendor lock-in or costly per-gigabyte pricing models. Key Capabilities \* Unified Data Fabric: Centralizes collection and delivery of logs, metrics, and events from any source to any destination. \* Flexible Routing: Dynamically routes data to multiple targets including Splunk, Elasticsearch, Snowflake, or S3-compatible data lakes. \* Transformation and Enrichment: Applies parsing, filtering, redaction, and enrichment rules in-stream for compliance and efficiency. \* Cost Optimization: Reduces SIEM and analytics storage costs through pre-processing, sampling, and tiered routing. \* Scalable and Secure: Built for enterprise workloads with role-based access control (RBAC), audit logging, and high-throughput performance. \* Hybrid Deployment: Operates natively in cloud or on-prem environments with the same configuration and governance framework. Value to Organizations Ingext enables enterprises to reduce cost, simplify complexity, and future-proof data operations. By decoupling collection from storage, it empowers teams to evolve their analytics tools and infrastructure without re-architecting data flows. The result is a streamlined, compliant, and transparent data ecosystem that ensures every event—no matter its source—can be used effectively where it matters most. **Seller Details:** - **Seller:** [Fluency](https://www.g2.com/sellers/fluency-005ac1a5-1603-4d37-864e-cca5c004f384) - **Year Founded:** 2009 - **HQ Location:** Dallas, US - **LinkedIn® Page:** https://www.linkedin.com/company/fluency-corp-dynamic-customized-private-language-lessons-at-your-home-office-or-online/ (22 employees on LinkedIn®) ### 2. [Kamon](https://www.g2.com/products/kamon/reviews) At Kamon we help developers find performance bottlenecks and errors in microservices. And we make it very easy and effortless: from clueless about what went wrong to solving issues in a few clicks Spend less time firefighting and more time writing code! **Seller Details:** - **Seller:** [Kamon](https://www.g2.com/sellers/kamon) - **HQ Location:** Zagreb, HR - **LinkedIn® Page:** https://www.linkedin.com/company/kamon-io/ (2 employees on LinkedIn®) ### 3. [Masthead](https://www.g2.com/products/masthead/reviews) Masthead Data is data observability platform for data teams on Google Cloud. Detect anomalies, observe pipelines, optimize compute costs. Our automated, ML-driven approach to data observability allows teams to catch and resolve data incidents in real time, while simultaneously optimizing Google BigQuery compute costs and maximizing ROI from their data platforms. The no-code implementation starts delivering results within minutes, and Masthead never needs read access to your data, meaning it is instantly compliant with privacy and security requirements. **Seller Details:** - **Seller:** [Masthead Data](https://www.g2.com/sellers/masthead-data) - **Year Founded:** 2022 - **HQ Location:** Toronto, CA - **LinkedIn® Page:** https://www.linkedin.com/company/masthead-data (12 employees on LinkedIn®) ### 4. [MetricSign](https://www.g2.com/products/metricsign/reviews) MetricSign is a monitoring and incident detection tool built for data engineers and BI developers who manage Power BI workspaces backed by multi-layer pipelines. When a Power BI dataset refresh fails, most teams find out from a stakeholder message. MetricSign finds out before that happens — and tells you why: was it a gateway credential expiry, an ADF pipeline failure, a dbt model error, or a Fabric capacity limit? You get one incident with the exact error code, the affected dataset, and suggested next steps. No log-trawling across five tools. \*\*What MetricSign monitors:\*\* - Power BI dataset refreshes — failures, slow refreshes, missed schedules - Azure Data Factory pipelines — run failures, activity errors - Databricks jobs — failures and slow runs - dbt Cloud jobs — run failures with step-level error detail - Microsoft Fabric pipelines and dataflows - End-to-end lineage: data source → pipeline → dataset → report \*\*How it works:\*\* Connect Power BI via Microsoft OAuth in under 2 minutes. MetricSign pulls workspace metadata, sets baseline refresh times per dataset, and starts detecting anomalies. No agents. No code. No credit card required. \*\*Who uses it:\*\* Data engineers and BI developers in organizations with 10–500 Power BI users, typically in teams where one engineer manages 20–200 datasets and needs to know about failures without checking Power BI Service manually. \*\*Alerts:\*\* Email, Telegram, webhook \*\*Pricing:\*\* Free plan available. Paid plans from €69/month. **Seller Details:** - **Seller:** [WNK Data Consultancy](https://www.g2.com/sellers/wnk-data-consultancy) - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (2 employees on LinkedIn®) ### 5. [ObserveNow](https://www.g2.com/products/observenow/reviews) Open source based observability stack featuring logs, traces and metrics – all under one roof. Observe any cloud infrastructure, VM, bare-metal servers, databases, or lambda functions with ObserveNow’s integrations available out of the box. Start observing at scale within minutes. **Seller Details:** - **Seller:** [OpsVerse](https://www.g2.com/sellers/opsverse) - **Year Founded:** 2021 - **HQ Location:** Redwood City, US - **LinkedIn® Page:** https://www.linkedin.com/company/opsverse/ (14 employees on LinkedIn®) ### 6. [Orchestra](https://www.g2.com/products/orchestra-orchestra/reviews) Orchestra is a lightweight orchestration and observability platform which gives real-time complete visibility for your entire data stack. We automate your orchestration, monitoring, and metadata collection to allow Data Teams spend less time fixing broken things and more time on what matters: building. Orchestra decouples orchestration from the rest of your stack which allows you to get all the power of a fully-featured workflow orchestrator without any of the pain. Build DAGs, connect up your stack, make a ☕ sit-back and relax The platform removes boilerplate orchestration logic and adds powerful metadata so data teams deliver robust, scalable data products backed by enterprise orchestration and observability. Find our more at: https://www.getorchestra.io/ **Average Rating:** 4.8/5.0 **Total Reviews:** 3 **User Satisfaction Scores:** - **Ease of Admin:** 10.0/10 (Category avg: 8.8/10) **Seller Details:** - **Seller:** [Orchestra](https://www.g2.com/sellers/orchestra-3e1057dc-7c1d-4451-89a9-a90f17f4ffbd) - **Year Founded:** 2023 - **HQ Location:** London, GB - **LinkedIn® Page:** https://www.linkedin.com/company/orchestra-go (15 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Mid-Market #### Pros & Cons **Pros:** - Automation (1 reviews) - Data Pipelining (1 reviews) - Ease of Use (1 reviews) - Easy Setup (1 reviews) - Efficiency (1 reviews) ### 7. [Qualdo-DRX](https://www.g2.com/products/qualdo-drx/reviews) Qualdo-DRX enables enterprises to easily monitor mission-critical issues, drifts, anomalies, errors, data quality & data reliability. This point-and-click product easily integrates with other enterprise products, alerts & notifies by monitoring 75+ metrics for data observability, continuously, is fully compliant, and never exports customer data. Qualdo-DRX tracks and traces the health of data and sends notifications in autopilot mode. **Seller Details:** - **Seller:** [Saturam](https://www.g2.com/sellers/saturam-27a17ecf-2e31-4069-b777-fda9e1a51ed9) - **HQ Location:** N/A - **Twitter:** @qualdo_ai (46 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®) ### 8. [Rudol](https://www.g2.com/products/rudol-rudol/reviews) Unlock the real power of your Data In today's data-driven landscape, the quality of your data is paramount. Poor data quality can lead to wrong business decisions, poor quality software or biased AI trainings, due to inaccurate, incomplete, or unreliable information. Enter Rudol, your data quality partner, designed to elevate your data quality game to new heights. Rudol is a comprehensive data quality platform that empowers organizations to maximize the value of their data. It's tailor-made for enterprises that recognize the importance of data quality, from improving decision-making to regulatory compliance, machine learning training or simply reducing problems in published software. And it does it for your whole organization, because it requires no technical background or coding skills whatsoever, its completely self service with 24/7 support, and all user accounts are Free, because the subscription cost is determined by the volume of your Data, enabling your whole structure to be part of the process. The foundation of data quality is understanding the landscape of your Assets. Rudol's Data Catalog allows organizations to bring order to their stack, by adding data sources from the most popular technologies, whether it's structured SQL databases, spreadsheets, dashboards, or even streaming sources. Then teams can perform Governance processes and define Owners, classify under Domains or Tags, put sensitive labels and help teams discover unknown sources for their projects. For those who don't want to have another browser tab opened, Rudol provides Slack, Microsoft Teams and Google Chrome plugins with vast functionalities, so you can find and share resources while chatting with another team member, or in your browser as a sidebar, while using your favorite analytics platform. Enabling Data Quality is a tedious process, Business Stakeholders have to chime in trying to translate their vision into technical requirements, and Software Engineers have to interpret those requirements, for coding boring, repetitive and time consuming scripts. This process is done with friction, and is very difficult to maintain over time, so Rudol bypasses this process by giving Business Stakeholders easy to build Validations that require no coding background and are extremely easy to configure. Choose from more than 15 Business Rules Validations or let Rudol parse your Data to pre configure some of them, the process takes less than 3 minutes and you can massively configure Validations to all your Assets in an instant. Releasing your Data Team from this repetitive tasks is crucial for optimizing their work and getting more value out of the practice, that's why Rudol also offers AI Validations to detect Anomalies where no business rules are defined. Use one of our 3 models to detect inconsistencies where not even Business Stakeholders can notice, and proactively notify your interested roles to identify hidden problems or false positives, because the models learn and improve with your feedback. Rudol also offers Lineage level traceability for Root Cause and Impact Analysis, allowing you to trace data from source to destination across data pipelines. Understand the upstream and downstream implications of any data issue, promoting accountability and transparency, or copy Validations accross your pipeline flow for higher quality coverage. With Rudol, Data Quality becomes accesible and easy to execute. It's designed for all levels of technical expertise, allowing everyone in your organization to participate in maintaining data quality. Rudol enhances decision-making, reduces infrastructure costs, and empowers organizations to make the most out of their data. Don't let poor data quality hinder your success. Choose Rudol and enable the real power of your Data. **Average Rating:** 5.0/5.0 **Total Reviews:** 1 **Seller Details:** - **Seller:** [Rudol](https://www.g2.com/sellers/rudol) - **Year Founded:** 2022 - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/rudol (7 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Small-Business ### 9. [Syren Data Quality Application](https://www.g2.com/products/syren-data-quality-application/reviews) With infinite data being generated every second, enterprises struggle to steer clear of data inconsistencies or outdated information. Syren’s DQS is designed to help organizations ensure that their data is accurate, reliable, and fit for intended purposes. By leveraging its profiling, cleansing, matching, and integration capabilities, Syren improves the consistency, integrity, and quality of data. **Seller Details:** - **Seller:** [Syren Cloud](https://www.g2.com/sellers/syren-cloud) - **Year Founded:** 2020 - **HQ Location:** Bellevue, US - **LinkedIn® Page:** https://www.linkedin.com/company/syrencloud/ (346 employees on LinkedIn®) ### 10. [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:** - **Ease of Admin:** 9.2/10 (Category avg: 8.8/10) **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 ## Parent Category [IT Management Software](https://www.g2.com/categories/it-management) ## Related Categories - [Data Quality Tools](https://www.g2.com/categories/data-quality) - [Database Monitoring Tools](https://www.g2.com/categories/database-monitoring) - [DataOps Platforms](https://www.g2.com/categories/dataops-platforms) --- ## Buyer Guide ### What You Should Know About Data Observability Software ### Data Observability Software FAQs ### What’s the most recommended customer success platform for SaaS companies? For software teams prioritizing data accuracy, operational visibility, and rapid issue resolution, top data observability platforms on G2 include: - [Monte Carlo](https://www.g2.com/products/monte-carlo/reviews) focuses exclusively on data observability, providing automated monitoring, anomaly detection, and data lineage to help teams catch and resolve data issues before they impact users. - [Metaplane](https://www.g2.com/products/metaplane/reviews) delivers end-to-end data observability with features like schema change detection, freshness monitoring, and anomaly detection, enabling teams to maintain data quality effectively. - [Acceldata](https://www.g2.com/products/acceldata/reviews) combines data quality monitoring, pipeline performance, and infrastructure health insights in one platform, helping software companies ensure their data operations run smoothly at scale. ### What’s the best data observability software for small businesses? For small businesses aiming to maintain data quality, monitor pipelines, and catch issues early without complex setup, [leading small business data observability solutions](https://www.g2.com/categories/data-observability/small-business) include: - [Bigeye](https://www.g2.com/products/bigeye/reviews) combines automated anomaly detection and root cause analysis in a platform that makes data reliability accessible without requiring deep technical resources, which is great for scaling teams. - [IBM Databand](https://www.g2.com/products/ibm-databand/reviews) delivers proactive monitoring and automated alerts while integrating easily with existing data pipelines, making it approachable for growing businesses with limited engineering support. - [Monte Carlo](https://www.g2.com/products/monte-carlo/reviews) offers a powerful but flexible solution with automated monitoring, data lineage, and incident resolution features. Although enterprise-ready, it also provides packages suitable for fast-growing small companies.