Best Data Warehouse Solutions for Small Business

How Many Data Warehouse Solutions Products Does G2 Track?

Total Products under this Category: 168

Category Stats (Nov 2026)

  • Average Rating: 4.38/5 The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: Synopsis (+0.77%) - Among all products in this category, Synopsis recorded the largest rating increase compared to last month

Last updated: November 01, 2026

How Does G2 Rank Data Warehouse Solutions Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 9,400+ Authentic Reviews
  • 168+ 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.

G2 Grid® for Data Warehouse Solutions

G2 Grid® for Data Warehouse Solutions plotting products by satisfaction and market presence

Highlighted products: Google Cloud BigQuery, Databricks, Snowflake, IBM watsonx.data, SAP Datasphere, Amazon Redshift, Starburst, and Teradata Autonomous Knowledge Platform.

Underlying data: [Grid® JSON](https://www.g2.com/categories/data-warehouse/grids.json?focus%5B%5D=google-cloud-bigquery&focus%5B%5D=databricks&focus%5B%5D=snowflake&focus%5B%5D=ibm-watsonx-data&focus%5B%5D=sap-datasphere&focus%5B%5D=amazon-redshift&focus%5B%5D=starburst&focus%5B%5D=teradata-autonomous-knowledge-platform&segment=small-business)

Google Cloud BigQuery

BigQuery is an AI-ready, petabyte-scale, and cost-effective data warehouse that lets you run analytics over vast amounts of data in near real time. Store 10 GiB of data and run up to 1 TiB of queries for free per month.

Average Rating: 4.5/5.0

Total Reviews: 1,161

How Do G2 Users Rate Google Cloud BigQuery?

  • Ease of Use: 8.7/10 (Category avg: 8.8/10)
  • Data Governance: 8.7/10 (Category avg: 8.4/10)
  • Data Security: 9.1/10 (Category avg: 8.8/10)
  • Scalability: 9.1/10 (Category avg: 8.5/10)

Who Is the Company Behind Google Cloud BigQuery?

  • Seller: Google
  • Year Founded: 1998
  • HQ Location: Mountain View, CA
  • LinkedIn® Page: www.linkedin.com
    301,144 employees on LinkedIn®
  • Ownership: NASDAQ:GOOG
  • Phone: +1 (650) 253-0000

Who Uses This Product?

  • Who Uses This: Data Engineer, Data Analyst
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 38% Large, 35% Medium

What Do G2 Reviewers Say About Google Cloud BigQuery?

AI-generated summary from verified user reviews

Pros
  • Users value the ease of use of Google Cloud BigQuery, appreciating its intuitive interface and fast query execution.
  • Users admire the fast query performance of Google Cloud BigQuery, enhancing their experience with large datasets.
  • Users value the fast querying capabilities of Google Cloud BigQuery, enabling efficient analysis of large datasets.
  • Users value the seamless SQL integration of BigQuery, enhancing data analytics in the Google Cloud ecosystem.
  • Users value the query efficiency of Google Cloud BigQuery, enjoying fast performance on large datasets with ease.
Cons
  • Users find the costs can escalate quickly without careful query optimization and monitoring on Google Cloud BigQuery.
  • Users experience query issues leading to escalated costs and unexpected behavior with special characters in BigQuery.
  • Users find that costs can escalate quickly with Google Cloud BigQuery due to unoptimized queries and large datasets.
  • Users report that costs can escalate quickly due to needing careful optimization and monitoring for large-scale queries.
  • Users find the learning curve steep for Google Cloud BigQuery, requiring significant time to master its features.

What Are Recent G2 Reviews of Google Cloud BigQuery?

What Are G2 Users Discussing About Google Cloud BigQuery?

Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform 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 platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. Founded in 2013 by the original creators of Apache Spark™, Delta Lake, MLflow and Unity Catalog, Databricks is built on an open lakehouse architecture that brings data, analytics and AI together. The platform is used by data engineers, data scientists, analysts, developers, machine learning teams, AI teams and business users to collaborate across the full data and AI lifecycle. Key Databricks capabilities include: - Data engineering: Build, automate and manage reliable batch, streaming and real-time data pipelines. - Analytics and business intelligence: Run SQL analytics, create dashboards and enable business teams to explore data. - Data governance: Discover, secure and manage data and AI assets across teams, clouds and workloads. - Machine learning and AI: Develop models, build generative AI applications and create production-grade AI agents. - Data applications: Build and deploy data-driven applications using governed enterprise data. Available across AWS, Azure and Google Cloud, Databricks helps organizations work across clouds, reduce data silos and simplify collaboration across teams and tools. Customers use Databricks for use cases such as customer personalization, fraud detection, predictive maintenance, real-time analytics, cybersecurity, healthcare research, financial risk management, supply chain optimization and AI-powered decision-making. Databricks is used across industries including financial services, healthcare and life sciences, retail, manufacturing, energy and the public sector. Organizations use the platform to modernize data infrastructure, accelerate AI adoption and turn enterprise data into business value.

Average Rating: 4.6/5.0

Total Reviews: 1,376

How Do G2 Users Rate Databricks?

  • Ease of Use: 8.8/10 (Category avg: 8.8/10)
  • Data Governance: 8.9/10 (Category avg: 8.4/10)
  • Data Security: 8.9/10 (Category avg: 8.8/10)
  • Scalability: 9.2/10 (Category avg: 8.5/10)

Who Is the Company Behind Databricks?

  • Seller: Databricks Inc.
  • Company Website:
  • Year Founded: 2013
  • HQ Location: San Francisco, CA
  • LinkedIn® Page: www.linkedin.com
    14,336 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Senior Data Engineer
  • Top Industries: Information Technology and Services, Financial Services
  • Company Size: 47% Large, 39% Medium

What Do G2 Reviewers Say About Databricks?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the seamless integration of big data and AI in Databricks, enhancing collaboration and performance.
  • Users appreciate the ease of use of Databricks, valuing its seamless integration and fast performance.
  • Users appreciate the seamless integration of Databricks with big data processing and AI, enhancing collaboration and performance.
  • Users value the seamless collaboration features of Databricks, enhancing teamwork and data analysis across departments.
  • Users appreciate the seamless integration of big data processing and AI in Databricks, enhancing collaboration and efficiency.
Cons
  • Users find the learning curve steep with Databricks, requiring time and skills to adapt effectively.
  • Users note that the cost can scale quickly, making cost monitoring and control a significant challenge.
  • Users find the steep learning curve of Databricks challenging, requiring considerable effort to adapt for business use cases.
  • Users find the inadequate ingestion options for non-standard data sources a limitation in Databricks' functionality.
  • Users find Databricks' complexity challenging, especially for beginners and smaller teams trying to fine-tune the system.

What Are Recent G2 Reviews of Databricks?

What Are G2 Users Discussing About Databricks?

Snowflake

Snowflake makes enterprise AI easy, efficient and trusted. Thousands of companies around the globe, including hundreds of the world’s largest, use Snowflake’s AI Data Cloud to share data, build applications, and power their business with AI. The era of enterprise AI is here. Learn more at snowflake.com (NYSE: SNOW).

Average Rating: 4.6/5.0

Total Reviews: 731

How Do G2 Users Rate Snowflake?

  • Ease of Use: 9.0/10 (Category avg: 8.8/10)
  • Data Governance: 8.9/10 (Category avg: 8.4/10)
  • Data Security: 9.1/10 (Category avg: 8.8/10)
  • Scalability: 9.3/10 (Category avg: 8.5/10)

Who Is the Company Behind Snowflake?

  • Seller: Snowflake, Inc.
  • Company Website:
  • Year Founded: 2012
  • HQ Location: Menlo Park, California, United States
  • LinkedIn® Page: www.linkedin.com
    12,574 employees on LinkedIn®
  • Ownership: NYSE:SNOW

Who Uses This Product?

  • Who Uses This: Data Engineer, Data Analyst
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 45% Medium, 42% Large

What Do G2 Reviewers Say About Snowflake?

AI-generated summary from verified user reviews

Pros
  • Users value the ease of use of Snowflake, enjoying its user-friendly interface and seamless scalability for data analysis.
  • Users appreciate the flexible scalability of Snowflake, allowing independent adjustments to performance and efficient resource management.
  • Users value the effortless data management Snowflake offers, enabling quick analysis without infrastructure concerns.
  • Users appreciate the user-friendly interface of Snowflake, making navigation easy and intuitive for SQL tasks.
  • Users value the strong integration ecosystem of Snowflake, which enhances versatility and simplifies data workflows seamlessly.
Cons
  • Users find Snowflake to be expensive, as costs can escalate quickly without careful usage monitoring and optimization.
  • Users highlight the high costs associated with Snowflake, especially for unoptimized workloads and usage spikes.
  • Users find cost management challenging, as compute expenses can escalate quickly without careful monitoring and optimization.
  • Users find the learning curve for advanced features in Snowflake steep, especially for newcomers needing rapid proficiency.
  • Users find feature limitations in Snowflake, particularly in cost management and control over optimization and dynamic scripting.

What Are Recent G2 Reviews of Snowflake?

What Are G2 Users Discussing About Snowflake?

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IBM watsonx.data

IBM® watsonx.data® helps you access, integrate and understand all your data —structured and unstructured—across any environment. It optimizes workloads for price and performance while enforcing consistent governance across sources, formats and teams. Watch the demo to learn how watsonx.data empowers you to build gen AI apps and powerful AI agents. Free Trial available: https://ibm.biz/Watsonx-data_Trial

Average Rating: 4.4/5.0

Total Reviews: 171

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How Do G2 Users Rate IBM watsonx.data?

  • Ease of Use: 8.2/10 (Category avg: 8.8/10)
  • Data Governance: 9.5/10 (Category avg: 8.4/10)
  • Data Security: 9.4/10 (Category avg: 8.8/10)
  • Scalability: 9.1/10 (Category avg: 8.5/10)

Who Is the Company Behind IBM watsonx.data?

  • Seller: IBM
  • Company Website:
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®
  • Ownership: SWX:IBM

Who Uses This Product?

  • Who Uses This: Software Engineer, Software Developer
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 34% Small, 32% Large

What Do G2 Reviewers Say About IBM watsonx.data?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of IBM watsonx.data, facilitating efficient data management and analytics integration.
  • Users value the efficient querying and analytics capabilities of IBM watsonx.data, enhancing data handling for complex tasks.
  • Users value the efficient data management capabilities of IBM watsonx.data, enhancing analytics and reducing costs effectively.
  • Users value the robust integration with various AI tools, enhancing analytics and simplifying model management within IBM watsonx.data.
  • Users value the fast querying and analytics capabilities of IBM watsonx.data, enhancing insight extraction from large datasets.
Cons
  • Users face a steep learning curve with watsonx.data, especially regarding documentation and initial setup processes.
  • Users find the complexity of IBM watsonx.data challenging, requiring time and expertise for effective use.
  • Users find the pricing high and confusing, making it challenging for small teams to justify the expense.
  • Users face a difficult setup with IBM watsonx.data, requiring extensive configuration and detailed documentation for effective use.
  • Users find difficulty in setup and documentation, requiring time and expertise to effectively utilize watsonx.data.

What Are Recent G2 Reviews of IBM watsonx.data?

SAP Datasphere

SAP Datasphere is a unified service for data integration, cataloging, semantic modeling, data warehousing, and virtualizing workloads across all your data. It enables every data professional to deliver seamless and scalable access to mission-critical business data. SAP Datasphere, and its open data ecosystem, is the foundation for a business data fabric.

Average Rating: 4.2/5.0

Total Reviews: 162

How Do G2 Users Rate SAP Datasphere?

  • Ease of Use: 8.1/10 (Category avg: 8.8/10)
  • Data Governance: 8.6/10 (Category avg: 8.4/10)
  • Data Security: 8.7/10 (Category avg: 8.8/10)
  • Scalability: 8.1/10 (Category avg: 8.5/10)

Who Is the Company Behind SAP Datasphere?

  • Seller: SAP
  • Year Founded: 1972
  • HQ Location: Walldorf
  • LinkedIn® Page: www.linkedin.com
    149,349 employees on LinkedIn®
  • Ownership: NYSE:SAP
  • Phone: +1 (800) 872-1727

Who Uses This Product?

  • Who Uses This: Business Analyst
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 41% Large, 36% Medium

What Do G2 Reviewers Say About SAP Datasphere?

AI-generated summary from verified user reviews

Pros
  • Users value the ease of use of SAP Datasphere, finding it accessible and intuitive for analytics tasks.
  • Users highly value SAP Datasphere's seamless integration capabilities, enhancing data unification and analytics across various systems.
  • Users appreciate the unified data management of SAP Datasphere, enhancing governance and speeding up reliable insights delivery.
  • Users value the seamless integration and real-time insights of SAP Datasphere, enhancing decision-making and collaboration effectively.
  • Users value SAP Datasphere's seamless collaboration across systems, making data integration and insights delivery much more efficient.
Cons
  • Users experience slow performance in SAP Datasphere, particularly with large datasets and complex transformations.
  • Users find SAP Datasphere to be quite expensive, particularly challenging for smaller projects and teams.
  • Users experience performance issues with SAP Datasphere, noting inconsistencies and slowness with complex models and large datasets.
  • Users experience significant integration issues with SAP Datasphere, complicating data management and performance optimization.
  • Users find the complex setup of SAP Datasphere challenging, often struggling with vague error messages and tedious documentation.

What Are Recent G2 Reviews of SAP Datasphere?

What Are G2 Users Discussing About SAP Datasphere?

Starburst

Starburst is the data platform for analytics, applications, and AI, unifying data across clouds and on-premises to accelerate AI innovation. Organizations—from startups to Fortune 500 enterprises in 60+ countries—rely on Starburst for fast data access, seamless collaboration, and enterprise-grade governance on an open hybrid data lakehouse. Wherever data lives, Starburst unlocks its full potential, powering data and AI from development to deployment. By future-proofing data architecture, Starburst helps businesses fuel innovation with AI. Learn more at starburst.ai

Average Rating: 4.3/5.0

Total Reviews: 132

How Do G2 Users Rate Starburst?

  • Ease of Use: 8.8/10 (Category avg: 8.8/10)
  • Data Governance: 7.8/10 (Category avg: 8.4/10)
  • Data Security: 8.4/10 (Category avg: 8.8/10)
  • Scalability: 8.8/10 (Category avg: 8.5/10)

Who Is the Company Behind Starburst?

  • Seller: Starburst
  • Company Website:
  • Year Founded: 2017
  • HQ Location: Boston, MA
  • LinkedIn® Page: www.linkedin.com
    543 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Senior Data Engineer, Software Engineer
  • Top Industries: Information Technology and Services, Financial Services
  • Company Size: 42% Small, 36% Large

What Do G2 Reviewers Say About Starburst?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the fast querying capabilities of Starburst, enhancing efficiency across various complex data sources and queries.
  • Users value the query efficiency of Starburst, highlighting its speed and effectiveness in handling complex queries.
  • Users appreciate the seamless integrations of Starburst, enhancing usability and efficiency in data management.
  • Users appreciate the ease of use of Starburst, highlighting its simple setup and user-friendly features for managing data.
  • Users highly value the high performance with large datasets of Starburst, enhancing efficiency in data access and analytics.
Cons
  • Users often face query issues with Starburst, particularly with troubleshooting and performance during complex queries.
  • Users experience slow performance with Starburst, especially when handling large data sets and complex queries.
  • Users often struggle with query complexity in Starburst, leading to slower performance and troubleshooting challenges.
  • Users find the learning curve steep for Starburst, requiring significant time to grasp its complexities and features.
  • Users report performance issues with query execution and setup, affecting efficiency and integration capabilities.

What Are Recent G2 Reviews of Starburst?

What Are G2 Users Discussing About Starburst?

Amazon Redshift

Tens of thousands of customers use Amazon Redshift, a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. It is optimized for datasets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

Average Rating: 4.3/5.0

Total Reviews: 387

How Do G2 Users Rate Amazon Redshift?

  • Ease of Use: 8.6/10 (Category avg: 8.8/10)
  • Data Governance: 8.7/10 (Category avg: 8.4/10)
  • Data Security: 8.8/10 (Category avg: 8.8/10)
  • Scalability: 8.8/10 (Category avg: 8.5/10)

Who Is the Company Behind Amazon Redshift?

Who Uses This Product?

  • Who Uses This: Data Engineer, Software Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 40% Large, 39% Medium

What Do G2 Reviewers Say About Amazon Redshift?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Amazon Redshift, finding it simple to implement and manage effectively.
  • Users appreciate the smooth integrations of Amazon Redshift, enhancing efficiency and collaboration with various software platforms.
  • Users love the easy integrations with other software, enhancing their experience with Amazon Redshift and data management.
  • Users value the fast querying capabilities of Amazon Redshift, enhancing efficiency in handling large datasets effortlessly.
  • Users appreciate the impressive scalability of Amazon Redshift, enabling efficient handling of large data volumes effortlessly.
Cons
  • Users find the operational complexity of Amazon Redshift to be a significant challenge, requiring extensive optimization efforts.
  • Users note the feature limitations in Amazon Redshift, including data type restrictions and outdated Postgre setup.
  • Users face software limitations with Amazon Redshift, including costly scaling and restricted data type support.
  • Users face challenges with query issues, including optimization needs, concurrency management, and performance degradation with complex data.
  • Users note that query optimization demands significant effort and specialized knowledge, complicating overall user experience.

What Are Recent G2 Reviews of Amazon Redshift?

What Are G2 Users Discussing About Amazon Redshift?

Teradata Autonomous Knowledge Platform

Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI. Learn more at Teradata.com.

Average Rating: 4.3/5.0

Total Reviews: 354

How Do G2 Users Rate Teradata Autonomous Knowledge Platform?

  • Ease of Use: 8.3/10 (Category avg: 8.8/10)
  • Data Governance: 7.9/10 (Category avg: 8.4/10)
  • Data Security: 8.2/10 (Category avg: 8.8/10)
  • Scalability: 8.5/10 (Category avg: 8.5/10)

Who Is the Company Behind Teradata Autonomous Knowledge Platform?

Who Uses This Product?

  • Who Uses This: Data Engineer, Software Engineer
  • Top Industries: Information Technology and Services, Financial Services
  • Company Size: 69% Large, 22% Medium

What Do G2 Reviewers Say About Teradata Autonomous Knowledge Platform?

AI-generated summary from verified user reviews

Pros
  • Users praise the high performance of Teradata Autonomous Knowledge Platform, noting its speed and reliability in data analysis.
  • Users benefit from the high speed of Teradata Autonomous Knowledge Platform, enabling fast and efficient data analysis.
  • Users appreciate the high-performance analytics of Teradata's platform, benefiting from fast, scalable data analysis and management.
  • Users value the scalability of Teradata Autonomous Knowledge Platform, enabling efficient handling of complex analytics and workloads.
  • Users appreciate the ability to handle large datasets efficiently, enabling powerful analysis and fast data insights.
Cons
  • Users find the steep learning curve of Teradata Autonomous Knowledge Platform challenging, impacting initial productivity during adoption.
  • Users find the steep learning curve challenging, making advanced features difficult to navigate for non-technical users.
  • Users find the complexity of the Teradata Autonomous Knowledge Platform challenging, especially for non-technical users.
  • Users find Teradata Autonomous Knowledge Platform not user-friendly, particularly for non-technical users navigating its outdated interface.
  • Users criticize the outdated user interface, noting it lacks intuitiveness and is difficult for non-core data team members.

What Are Recent G2 Reviews of Teradata Autonomous Knowledge Platform?

What Are G2 Users Discussing About Teradata Autonomous Knowledge Platform?

IBM Db2

Built to run the world’s mission-critical workloads. Designed by the world’s leading database experts, IBM Db2 empowers developers, enterprise architects, and data engineers to run low-latency transactions and real-time analytics equipped for the most demanding workloads. From microservices to AI workloads, Db2 is the tested, resilient, and hybrid database providing the extreme availability, built-in refined security, effortless scalability, and intelligent automation for systems that run the world.

Average Rating: 4.1/5.0

Total Reviews: 600

How Do G2 Users Rate IBM Db2?

  • Ease of Use: 8.0/10 (Category avg: 8.8/10)
  • Data Governance: 8.7/10 (Category avg: 8.4/10)
  • Data Security: 9.0/10 (Category avg: 8.8/10)
  • Scalability: 8.6/10 (Category avg: 8.5/10)

Who Is the Company Behind IBM Db2?

  • Seller: IBM
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®
  • Ownership: SWX:IBM
  • Phone: 1-866-277-7488

Who Uses This Product?

  • Who Uses This: Senior Software Engineer, Software Engineer
  • Top Industries: Information Technology and Services, Banking
  • Company Size: 66% Large, 21% Medium

What Do G2 Reviewers Say About IBM Db2?

AI-generated summary from verified user reviews

Pros
  • Users commend the high performance of IBM Db2, ensuring efficient data management and reliability for critical workloads.
  • Users value the high reliability of IBM Db2, ensuring consistent performance even during system failures.
  • Users admire the scalability of IBM Db2, facilitating easy management of large databases as business needs grow.
  • Users value the strong security measures of IBM Db2, ensuring robust data protection and integrity.
  • Users find IBM Db2 easy to use and integrate, appreciating its smooth functionality and developer-friendly features.
Cons
  • Users find the complex setup of IBM Db2 challenging, leading to frustrations during initial implementation and administration.
  • Users find the high costs of IBM Db2 a significant barrier, impacting overall satisfaction with the product.
  • Users face a steep learning curve with IBM Db2, making it challenging to master despite its advanced features.
  • Users find IBM Db2 complex to set up, with a steep learning curve and potential vendor lock-in challenges.
  • Users face a difficult setup process with IBM Db2, creating challenges during installation and administration.

What Are Recent G2 Reviews of IBM Db2?

What Are G2 Users Discussing About IBM Db2?

VMware Greenplum

Advanced analytics meets traditional business intelligence with VMware Greenplum, the world’s first fully-featured, multi-cloud, massively parallel processing (MPP) data platform based on the open source Greenplum Database. Greenplum provides comprehensive and integrated analytics on multi-structured data. Powered by one of the world’s most advanced cost-based query optimizers, VMware Greenplum delivers unmatched analytical query performance on massive volumes of data.

Average Rating: 4.3/5.0

Total Reviews: 55

How Do G2 Users Rate VMware Greenplum?

  • Ease of Use: 8.4/10 (Category avg: 8.8/10)
  • Data Governance: 9.3/10 (Category avg: 8.4/10)
  • Data Security: 9.3/10 (Category avg: 8.8/10)
  • Scalability: 8.7/10 (Category avg: 8.5/10)

Who Is the Company Behind VMware Greenplum?

  • Seller: Broadcom
  • Year Founded: 1991
  • HQ Location: San Jose, CA
  • LinkedIn® Page: www.linkedin.com
    44,602 employees on LinkedIn®
  • Ownership: NASDAQ: CA
  • Phone: +1 800 225-5224

Who Uses This Product?

  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 49% Large, 31% Medium

What Are Recent G2 Reviews of VMware Greenplum?

What Are G2 Users Discussing About VMware Greenplum?

Cloudera

Cloudera is the only hybrid data and AI platform company that large organizations trust to bring AI to their data anywhere it lives. Unlike other providers, Cloudera delivers a consistent cloud experience that converges public clouds, on-prem data centers, and the edge, leveraging a proven open-source foundation. As the pioneer in big data, Cloudera empowers businesses to apply AI and assert control over 100% of their data, in all forms, improving security, governance, and real-time and predictive insights. The world’s largest brands across all industries rely on Cloudera to transform decision-making and ultimately boost bottom lines, safeguard against threats, and save lives. Cloudera Anywhere Cloud™: Build and scale applications across any environment. The modular hybrid data and AI platform engineered for the agentic era empowers teams to deploy production-grade data and AI workloads across multi-cloud, on-premises, and sovereign environments while maintaining digital sovereignty. The Cloudera data and AI platform includes: Cloudera AI: Deploy and scale any AI model, anywhere. Cloudera brings compute to governed data where it lives for Private AI anywhere by design. Complete control, security, and governance of mission-critical data, models, agents, and inference ensure faster sovereign AI deployments. Cloudera Data-in-Motion: Make fast decisions from real-time data anywhere. Move data with any structure from any source to any destination seamlessly across hybrid environments, enabling in-the-moment business-critical decisions by processing and analyzing real-time data anywhere, from the edge to AI, as business happens. Cloudera Open Data Lakehouse: Process any data, anywhere, for actionable insights. Make smart decisions with an open data lakehouse powered by Apache Iceberg that delivers trusted, reliable, and unified data to fuel agents, AI applications, and analytics, improving collaboration, breaking silos, and simplifying sharing. Cloudera Unified Data Fabric: Unify security and governance across the entire data estate. Move beyond fragmented data management: Break down silos and connect disparate data sources intelligently and securely to provide a unified view of all organizational data and centralized end-to-end control across complex hybrid data environments.

Average Rating: 4.2/5.0

Total Reviews: 208

How Do G2 Users Rate Cloudera?

  • Ease of Use: 8.4/10 (Category avg: 8.8/10)
  • Data Governance: 8.9/10 (Category avg: 8.4/10)
  • Data Security: 9.2/10 (Category avg: 8.8/10)
  • Scalability: 9.4/10 (Category avg: 8.5/10)

Who Is the Company Behind Cloudera?

  • Seller: Cloudera
  • Company Website:
  • Year Founded: 2008
  • HQ Location: Santa Clara, CA
  • LinkedIn® Page: www.linkedin.com
    3,505 employees on LinkedIn®
  • Phone: 888-789-1488

Who Uses This Product?

  • Who Uses This: Data Engineer, Software Engineer
  • Top Industries: Information Technology and Services, Banking
  • Company Size: 39% Large, 33% Small

What Do G2 Reviewers Say About Cloudera?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Cloudera, enjoying its straightforward installation and maintenance for analytics.
  • Users commend Cloudera for its exceptional scalability, enabling seamless integration and efficient big data management.
  • Users commend Cloudera for its robust security, ideal for high-scale enterprise-level data engineering tasks.
  • Users appreciate the easy and secure data management provided by Cloudera, enabling smart analytics and decision-making.
  • Users value the user-friendly features of Cloudera, which simplify big data handling and improve workflow efficiency.
Cons
  • Users express concerns over the high costs associated with Cloudera, making it less accessible for some.
  • Users find Cloudera to have a complex setup and operational challenges, especially for inexperienced professionals.
  • Users find Cloudera setup to be difficult to learn, especially for beginners navigating its complex interface.
  • Users find the documentation lacking, which hampers navigating data configurations and resolving errors effectively.
  • Users face significant access issues with Cloudera, including limited documentation and authorization errors during task execution.

What Are Recent G2 Reviews of Cloudera?

What Are G2 Users Discussing About Cloudera?

SQL Server 2019

Parallel Data Warehouse offers scalability to hundreds of terabytes and high performance through a massively parallel processing architecture.

Average Rating: 4.5/5.0

Total Reviews: 78

How Do G2 Users Rate SQL Server 2019?

  • Ease of Use: 9.0/10 (Category avg: 8.8/10)
  • Data Governance: 8.5/10 (Category avg: 8.4/10)
  • Data Security: 9.0/10 (Category avg: 8.8/10)
  • Scalability: 8.8/10 (Category avg: 8.5/10)

Who Is the Company Behind SQL Server 2019?

  • Seller: Microsoft
  • Year Founded: 1975
  • HQ Location: Redmond, Washington
  • LinkedIn® Page: www.linkedin.com
    232,750 employees on LinkedIn®
  • Ownership: MSFT
  • Phone: +1 (877) 276-2464

Who Uses This Product?

  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 37% Medium, 35% Large

What Do G2 Reviewers Say About SQL Server 2019?

AI-generated summary from verified user reviews

Pros
  • Users value the seamless data integration in SQL Server 2019, enhancing performance and facilitating smooth backend development.
  • Users value the advanced indexing and optimized data retrieval in SQL Server 2019 for managing complex queries effectively.
Cons
  • Users find the high licensing costs of SQL Server 2019 challenging, especially for smaller project budgets.

What Are Recent G2 Reviews of SQL Server 2019?

What Are G2 Users Discussing About SQL Server 2019?

Tembo

Tembo is a multi-workload Postgres managed service that enables organizations to harness the full power of Postgres for transactional, analytical, and AI workloads. With robust SaaS and self hosted deployment options, Tembo enables everyone – from the smallest startups to the Fortune 500 – to go “all in” on Postgres, achieving unprecedented stability and efficiency across a variety of applications and use cases. With Tembo, customers get all the stability, reliability, and extensibility of Postgres open source with enhanced observability, compliance, and developer experience.

Average Rating: 4.7/5.0

Total Reviews: 26

How Do G2 Users Rate Tembo?

  • Ease of Use: 9.4/10 (Category avg: 8.8/10)
  • Data Governance: 9.6/10 (Category avg: 8.4/10)
  • Data Security: 9.6/10 (Category avg: 8.8/10)
  • Scalability: 9.3/10 (Category avg: 8.5/10)

Who Is the Company Behind Tembo?

  • Seller: Tembo
  • Year Founded: 2022
  • HQ Location: Cincinnati, US
  • LinkedIn® Page: www.linkedin.com
    32 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software
  • Company Size: 85% Small, 15% Medium

What Do G2 Reviewers Say About Tembo?

AI-generated summary from verified user reviews

Pros
  • Users praise Tembo for its ease of use, enabling seamless organization, collaboration, and quick navigation.
  • Users love the intuitive interface of Tembo, making organization and team collaboration effortless and user-friendly.
  • Users appreciate the extensive integrations Tembo offers, enhancing collaboration and streamlining data management effortlessly.
  • Users highlight the ease of setup with Tembo, enabling quick deployment and smooth integration of services.
  • Users praise Tembo for its easy integrations, allowing seamless connections and efficient data management across platforms.
Cons
  • Users find Tembo's limited flexibility concerning, particularly due to restricted integration and customization options.
  • Users find the limited AWS dependency of Tembo restrictive, hoping for broader integration with other cloud services.
  • Users highlight the limited cloud integration of Tembo, focusing solely on AWS and lacking support for other services.
  • Users find Tembo to be expensive, with costs varying and potentially burdensome for small businesses and startups.
  • Users find the limited customization options in Tembo frustrating compared to other tools, affecting their overall experience.

What Are Recent G2 Reviews of Tembo?

Rocket Vertica

Vertica is the unified analytics platform, based on a massively scalable architecture with a broad set of analytical functions spanning event and time series, pattern matching, geospatial, and built-in machine learning capability. Vertica enables data analytics teams to easily apply these powerful functions to large and demanding analytical workloads, arming them and their customers with predictive business insights. Vertica provides a unified analytics platform across major public clouds and on-premises data centers, and integrates data in cloud object storage and HDFS without forcing any data movement. Available as a SaaS option, or as a customer-managed platform, Vertica helps teams combine growing data siloes for a more complete view of available data. Vertica features separation of compute and storage, so teams can spin up storage and compute resources as needed, then spin down afterwards to reduce costs.

Average Rating: 4.3/5.0

Total Reviews: 195

How Do G2 Users Rate Rocket Vertica?

  • Ease of Use: 8.5/10 (Category avg: 8.8/10)
  • Data Governance: 8.3/10 (Category avg: 8.4/10)
  • Data Security: 8.5/10 (Category avg: 8.8/10)
  • Scalability: 8.3/10 (Category avg: 8.5/10)

Who Is the Company Behind Rocket Vertica?

Who Uses This Product?

  • Who Uses This: Senior Software Engineer, Data Engineer
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 44% Large, 39% Medium

What Are Recent G2 Reviews of Rocket Vertica?

What Are G2 Users Discussing About Rocket Vertica?

Aden

Aden is the first self-evolving execution engine designed to move AI agents beyond static, brittle flowcharts. Instead of breaking when an API changes or a prompt is ambiguous, the system uses a "Queen Bee" architecture to synthesize new logic in real-time. It captures failure traces, updates its internal Goal Object, and automatically refactors its own code to overcome obstacles. By shifting from manual orchestration to autonomous evolution, Aden enables engineers to focus on defining outcomes rather than babysitting brittle scripts.

Average Rating: 5.0/5.0

Total Reviews: 34

How Do G2 Users Rate Aden?

  • Ease of Use: 9.7/10 (Category avg: 8.8/10)
  • Data Governance: 9.5/10 (Category avg: 8.4/10)
  • Data Security: 9.3/10 (Category avg: 8.8/10)
  • Scalability: 9.4/10 (Category avg: 8.5/10)

Who Is the Company Behind Aden?

  • Seller: Acho
  • Year Founded: 2020
  • HQ Location: Boston, MA
  • LinkedIn® Page: www.linkedin.com
    57 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Information Technology and Services
  • Company Size: 68% Small, 18% Medium

What Are Recent G2 Reviews of Aden?

What Are G2 Users Discussing About Aden?

Shalaka Joshi
SJ
Researched and written by Shalaka Joshi
Updated
Reviews & FAQs

Reviews Summary: The Best Data Warehouse Software for Small-Business Businesses

Thanks to 7124 Data Warehouse software reviews and associated data from users working for small-sized companies, at G2 we have some of the most definitive data on the best Data Warehouse software for the smaller space. We have identified 18 individual Data Warehouse products offering the features, pricing and support that Small-Business companies look for when comparing Data Warehouse software and solutions. These reviews are generated using the qualitative and quantitative feedback from G2 members working in small-sized companies and who have used these Data Warehouse software products.

When G2 reviewers submit their Data Warehouse software reviews, they often provide information on the type of company they work for and what market segment they belong to. We break these different market segments into three distinct groups:

  • Small Business Data Warehouse Software Reviews (< 50 employees)
  • smaller Data Warehouse Software Reviews (51-1,000 employees)
  • Enterprise Data Warehouse Software Reviews (1,001+ employees)

smaller businesses have their own unique requirements when it comes to Data Warehouse software compared to small or enterprise companies. That is why these individual small-sized company Data Warehouse software reviews are especially helpful when comparing product set up, ease of use and overall cost.

Below you will find FAQs and review snippets for Data Warehouse software products that work well in smaller environments. These reviews are written by real G2 users working for these Small-Business companies who have real-world experience with these Data Warehouse software products.

FAQs About Data Warehouse Software for Small-Business Businesses

Q. What are the best Data Warehouse software products for small-sized businesses, according to G2 reviewers?
  • Google Cloud BigQuery - 4.4-stars, 161 reviews (24% from smaller reviewers)
  • Databricks - 4.6-stars, 62 reviews (12% from smaller reviewers)
  • Snowflake - 4.4-stars, 76 reviews (12% from smaller reviewers)
  • IBM watsonx.data - 4.6-stars, 31 reviews (38% from smaller reviewers)
  • SAP Datasphere - 4.1-stars, 34 reviews (22% from smaller reviewers)
Q. What are the least-liked Data Warehouse software products for professionals at small-sized companies, based on the overall G2 rating?
  • Roghnu - 5.0-stars, 15 reviews (33% from smaller reviewers)
  • Panoply - 4.5-stars, 37 reviews (47% from smaller reviewers)
  • Mozart Data - 4.7-stars, 31 reviews (52% from smaller reviewers)
  • Rocket Vertica - 4.4-stars, 24 reviews (15% from smaller reviewers)
  • Aden - 5.0-stars, 23 reviews (68% from smaller reviewers)
Q. What are the highest-rated Data Warehouse software tool features according to employees at Small-Business companies?
  • Data Security - 4.5-stars
  • Data Integration - 4.5-stars
  • Data Quality - 4.5-stars
Q. What are the features that are rated lowest by employees at Small-Business companies?
  • AI Text Generation - 3.8-stars
  • AI Text Summarization - 3.9-stars
  • On-Premise - 4.0-stars
Q. How many Data Warehouse software reviews are from users working in smaller companies?

685 out of all Data Warehouse software reviews on G2 are from users working in Small-Business companies (10%).

Here's What Reviewers Working at smaller Businesses Have to Say About Data Warehouse Software

What Small-Business Professionals Liked What Small-Business Professionals Disliked

Aden: “After years of Excel blowing up on large datasets, finally along comes Achio.io. Thank goodness!”

Read Review

Google Cloud BigQuery: “It is often difficult to navigate the interface, especially if there is a greater amount of content coming in to manage. Consequently, the invoicing and the pricing to manage this content increases which can become overwhelming and difficult to track.”

Read Review

Keboola: “I like Keboola's clear interface and the wide range of data connections. The ready-made connections to services like Google Analytics and ERP systems are very good. It simplifies working with data, allowing us to get data from the system with just a few clicks.”

Read Review

Piloterr: “When their API breaks down, which happens often they will still expire the credits, lost several dollars on this product”

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Snowflake: “Snowflake is a great data platform, I feel its transparency on cost and ability to run queries in the faster way is great”

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SAP Datasphere: “Certain tasks require switching between multiple interfaces, and performance can vary depending on the data virtualization approach. Documentation and examples could also be more detailed, especially for complex modeling scenarios. While the platform is evolving quickly, these areas can slow down adoption.”

Read Review
Recommendations To Others Problems Solved & Benefits

Roghnu: “I recommend having discovery calls to talk through your use cases. Their team is very capable at coming up with elegant solutions.”

Read Review

EnrichmentAPI: “We try to aggregate profile data from the web on Scrapingdog ourselves, but we haven’t been successful. Because the data coming through our Profile API was often incomplete, many customers ended up churning. EnrichmentAPI solved a real problem for us by addressing that missing-data gap, and it’s economical as well, so it fits into our pricing dynamics. As I mentioned, incomplete data was a major issue on our side. Once EnrichmentAPI handled that part, our Profile API became more complete and our conversion rate went up as a result. Truly an amazing service!”

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Amazon Redshift: “It's ok ok”

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Starburst: “I use Starburst to query and analyze data from different sources easily, saving time and simplifying data analysis without moving everything into one place. It provides flexibility and fits well into our data workflow.”

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Roghnu: “You cannot go wrong with them by your side. They offer excellent service and make it accessible to understand your business setup.”

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Starburst: “Starburst helps us access and query data from multiple sources through a single platform without constantly moving or copying the data. This reduces the dependency on complex ETL pipelines, saves time for the data team, and makes analytics faster. It is especially useful when we need to work with distributed datasets across different systems”

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