Top Free Data Warehouse Solutions

How Many Data Warehouse Solutions Products Does G2 Track?

Total Products under this Category: 122

Category Stats (Sep 2026)

  • Average Rating: 4.37/5 The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: Cloudera (+2.21%) - Among all products in this category, Cloudera recorded the largest rating increase compared to last month

Last updated: September 01, 2026

How Does G2 Rank Data Warehouse Solutions Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 7,500+ Authentic Reviews
  • 122+ 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: Databricks, Google Cloud BigQuery, Snowflake, SAP Datasphere, IBM watsonx.data, Amazon Redshift, Teradata Autonomous Knowledge Platform, and VMware Greenplum.

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

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: 1,330

How Do G2 Users Rate Databricks?

  • Ease of Use: 8.8/10 (Category avg: 8.7/10)
  • 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
  • Twitter: @databricks
    92,269 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    14,336 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Data Analyst
  • Top Industries: Information Technology and Services, Financial Services
  • Company Size: 48% Large, 38% Medium

What Do G2 Reviewers Say About Databricks?

AI-generated summary from verified user reviews

Pros
  • Users enjoy the ease of use and extensive features of Databricks, streamlining data warehousing and machine learning tasks.
  • Users value the seamless integrations with AWS services that enhance efficiency and support diverse business needs.
  • Users appreciate the ease of use of Databricks, enhancing their experience with its intuitive interface and efficient features.
  • Users value the seamless collaboration provided by Databricks, enhancing teamwork on data projects and insights sharing.
  • Users value the effective data management features of Databricks, simplifying their workflows and enhancing decision-making.
Cons
  • Users face a steep learning curve with Databricks, as its complexity can be confusing for newcomers.
  • Users note that the cost of Databricks can be quite high, particularly for large data projects and limited free options.
  • Users express frustration over missing features in Databricks, limiting its effectiveness for complex deployments and custom setups.
  • Users find the steep learning curve of Databricks challenging, particularly for those unfamiliar with big data tools.
  • Users face unintuitive UI issues that lead to random errors and complicate the experience for non-technical users.

What Are Recent G2 Reviews of Databricks?

What Are G2 Users Discussing About Databricks?

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: 1,144

How Do G2 Users Rate Google Cloud BigQuery?

  • Ease of Use: 8.7/10 (Category avg: 8.7/10)
  • 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
  • Twitter: @google
    31,899,995 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    301,144 employees on LinkedIn®
  • Ownership: NASDAQ:GOOG

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, enabling fast analysis without needing to manage infrastructure.
  • Users appreciate the incredible speed of BigQuery, making data processing effortless and efficient for large datasets.
  • Users value the seamless integrations of Google Cloud BigQuery, enhancing analytics and supporting various data types effortlessly.
  • Users appreciate the fast querying capabilities of Google Cloud BigQuery, enabling quick analysis of massive datasets effortlessly.
  • Users value the query efficiency of BigQuery, enabling fast analysis of massive datasets with minimal effort.
Cons
  • Users find the cost structure expensive, especially with complex queries leading to rapidly escalating charges.
  • Users often face query issues with BigQuery, as inefficient queries can rapidly increase costs and complicate budgeting.
  • Users find the cost management challenging, facing unpredictable pricing and needing strict governance to maintain budgets.
  • Users face cost issues with Google Cloud BigQuery, often leading to unexpectedly high bills and budget management challenges.
  • Users find the steep learning curve for advanced features challenging, requiring significant time and effort to master.

What Are Recent G2 Reviews of Google Cloud BigQuery?

What Are G2 Users Discussing About Google Cloud BigQuery?

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: 713

How Do G2 Users Rate Snowflake?

  • Ease of Use: 9.0/10 (Category avg: 8.7/10)
  • Data Governance: 8.9/10 (Category avg: 8.4/10)
  • Data Security: 9.1/10 (Category avg: 8.8/10)
  • Scalability: 9.4/10 (Category avg: 8.5/10)

Who Is the Company Behind Snowflake?

  • Seller: Snowflake, Inc.
  • Company Website:
  • Year Founded: 2012
  • HQ Location: 135 Constitution Drive, Menlo Park CA
  • Twitter: @SnowflakeDB
    278 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    12,574 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Data Analyst
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 45% Medium, 43% Large

What Do G2 Reviewers Say About Snowflake?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Snowflake, which simplifies data sharing and enhances productivity across teams.
  • Users value the reliable features and user-friendly interface of Snowflake, enhancing data management and analytics efficiency.
  • Users value the seamless scalability of Snowflake, enabling efficient handling of large datasets and workload changes without performance loss.
  • Users value the fast and efficient data processing capabilities of Snowflake, enhancing their analysis experience significantly.
Cons
  • Users highlight the high costs of Snowflake, making it less accessible for smaller businesses with limited budgets.
  • Users find feature limitations in Snowflake, such as lack of code blocks and restricted permissions, frustrating.
  • Users often struggle with high costs due to unoptimized queries and inadequate cost control measures in Snowflake.
  • Users find the cost structure challenging, requiring time to optimize for efficient use of Snowflake.
  • Users find Snowflake's limited features in dynamic scripts and monitoring hinder flexibility and usability.

What Are Recent G2 Reviews of Snowflake?

What Are G2 Users Discussing About Snowflake?

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: 163

How Do G2 Users Rate SAP Datasphere?

  • Ease of Use: 8.1/10 (Category avg: 8.7/10)
  • Data Governance: 8.6/10 (Category avg: 8.4/10)
  • Data Security: 8.7/10 (Category avg: 8.8/10)
  • Scalability: 8.2/10 (Category avg: 8.5/10)

Who Is the Company Behind SAP Datasphere?

  • Seller: SAP
  • Year Founded: 1972
  • HQ Location: Walldorf
  • Twitter: @SAP
    297,052 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    149,349 employees on LinkedIn®
  • Ownership: NYSE:SAP

Who Uses This Product?

  • Who Uses This: Business Analyst
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 40% Large, 36% Medium

What Do G2 Reviewers Say About SAP Datasphere?

AI-generated summary from verified user reviews

Pros
  • Users find SAP Datasphere's ease of use enhances their workflow significantly compared to similar services.
  • Users value the easy integrations of SAP Datasphere, allowing seamless connectivity with ERP systems for enhanced data management.
  • Users value the seamless integration of diverse data sources in SAP Datasphere, enhancing data management and accessibility for analytics.
  • Users appreciate the business-contextualized data integration of SAP Datasphere, which simplifies analytics and promotes collaboration.
  • Users value the seamless collaboration of SAP Datasphere, making data access and integration efficient within the SAP ecosystem.
Cons
  • Users are frustrated by the slow performance of SAP Datasphere, especially when handling large datasets and complex tasks.
  • Users find the pricing expensive, which can make it challenging for new users to adopt SAP Datasphere effectively.
  • Users experience performance issues with SAP Datasphere, noting slow speeds and latency, especially with large datasets.
  • Users face integration issues with SAP Datasphere, finding it challenging to set up and connect various data sources.
  • Users find the complex setup of SAP Datasphere challenging, often leading to frustration during the initial configuration.

What Are Recent G2 Reviews of SAP Datasphere?

What Are G2 Users Discussing About SAP Datasphere?

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: 169

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How Do G2 Users Rate IBM watsonx.data?

  • Ease of Use: 8.2/10 (Category avg: 8.7/10)
  • Data Governance: 9.5/10 (Category avg: 8.4/10)
  • Data Security: 9.5/10 (Category avg: 8.8/10)
  • Scalability: 9.2/10 (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
  • Twitter: @IBMSecurity
    74,660 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®

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, finding it reliable and efficient for data management.
  • Users value the seamless data integration and user-friendly interface of IBM watsonx.data for efficient analytics.
  • Users appreciate the organized and efficient data management of IBM watsonx.data, simplifying analytics and enhancing team collaboration.
  • Users value the seamless data source integration of IBM watsonx.data, enhancing efficiency and flexibility in their workflows.
  • Users appreciate the flexible analytics capabilities of IBM watsonx.data, enabling faster insights from diverse data sources.
Cons
  • Users find the steep learning curve of IBM watsonx.data challenging, hindering easy adoption for newcomers.
  • Users find the complexity of setting up IBM watsonx.data a barrier, especially for newcomers and small teams.
  • Users find the pricing steep for IBM watsonx.data, especially for smaller businesses with limited resources.
  • Users find the difficult setup process time-consuming, with a steep learning curve and extensive documentation review required.
  • Users find performance tuning difficult with IBM watsonx.data, especially for beginners and teams with limited IT resources.

What Are Recent G2 Reviews of IBM watsonx.data?

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: 371

How Do G2 Users Rate Amazon Redshift?

  • Ease of Use: 8.7/10 (Category avg: 8.7/10)
  • Data Governance: 8.7/10 (Category avg: 8.4/10)
  • Data Security: 8.8/10 (Category avg: 8.8/10)
  • Scalability: 8.9/10 (Category avg: 8.5/10)

Who Is the Company Behind Amazon Redshift?

  • Seller: Amazon Web Services (AWS)
  • Year Founded: 2006
  • HQ Location: Seattle, WA
  • Twitter: @awscloud
    2,232,483 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    147,094 employees on LinkedIn®
  • Ownership: NASDAQ: AMZN

Who Uses This Product?

  • Who Uses This: Data Engineer, Senior Data 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 fast querying capabilities of Amazon Redshift, enjoying efficient and smooth data access for large datasets.
  • Users appreciate the seamless integrations of Amazon Redshift, enhancing functionality and efficiency across their data solutions.
  • Users appreciate the ease of use of Amazon Redshift, finding it simple to connect and manage data effectively.
  • Users appreciate the easy integrations with other software and AWS services, enhancing their data management experience.
  • Users appreciate the impressive speed and scalability of Amazon Redshift, enhancing their data warehousing experience significantly.
Cons
  • Users note notable feature limitations in Amazon Redshift, particularly in advanced analytics and cross-language coding.
  • Users find software limitations in Redshift, experiencing issues with performance, concurrency, and data type support.
  • Users face significant complexity in optimizations with Redshift, requiring extensive management and specialized knowledge for effective use.
  • Users face query issues, requiring significant time for optimization, tuning, and managing complexity and concurrency challenges.
  • Users face a significant query optimization challenge with Redshift, requiring considerable effort and specialized knowledge.

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: 8.7/10)
  • 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 highlight the extreme performance of Teradata Autonomous Knowledge Platform, emphasizing its speed in processing large data volumes.
  • Users value the high performance and scalability of Teradata for handling complex queries and data integration.
  • Users value the scalability of Teradata Autonomous Knowledge Platform, seamlessly integrating and managing vast data resources efficiently.
  • Users commend the extreme performance of Teradata, highlighting its speed in processing large datasets seamlessly.
  • Users value the fast processing of large datasets in Teradata, appreciating its stability and integration capabilities.
Cons
  • Users identify a steep learning curve for Teradata Autonomous Knowledge Platform, hindering new user adaptation and productivity.
  • Users find the steep learning curve of Teradata Autonomous Knowledge Platform challenging, especially for those less technically inclined.
  • Users find the complexity of the Teradata platform challenging, especially for non-technical users and new adopters.
  • Users struggle with the cost transparency of Teradata Autonomous Knowledge Platform, needing close management to avoid issues.
  • Users express concerns about the high cost of the Teradata Autonomous Knowledge Platform, highlighting affordability issues.

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: 8.7/10)
  • 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
  • Twitter: @IBMSecurity
    74,660 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®
  • Ownership: SWX:IBM

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 highlight the high performance of IBM Db2, appreciating its reliability and efficiency in managing large datasets.
  • Users praise IBM Db2 for its exceptional reliability, consistently delivering strong performance even under heavy workloads.
  • Users find IBM Db2 to be easy to use and integrate, enhancing daily tasks and overall efficiency.
  • Users commend the scalability of IBM Db2, ensuring excellent performance even with large datasets and enterprise workloads.
  • Users value the high availability of IBM Db2, ensuring seamless access to data even during outages.
Cons
  • Users express concern over feature limitations in IBM Db2, desiring quicker updates and improved management tools.
  • Users find IBM Db2's setup complex, facing high costs and limited documentation that complicate the user experience.
  • Users often find the complex setup of IBM Db2 challenging, requiring significant time and effort to manage effectively.
  • Users find the difficult setup of IBM Db2 challenging, often leading to frustration during initial configuration and administration.
  • Users feel that the expertise required for IBM Db2 makes it harder to find skilled specialists and implement new features.

What Are Recent G2 Reviews of IBM Db2?

What Are G2 Users Discussing About IBM Db2?

Dremio

Dremio is the pioneer of The Agentic Lakehouse—the only data platform built for agents, managed by agents. Organizations need to transform ideas into actions at unprecedented speed—Dremio delivers this agility by equipping AI agents with federated data access, unstructured data processing, and rich business context through its AI Semantic Layer. In the agentic-era, data engineering teams can’t manually tune performance for thousands of users and agents asking unpredictable questions every second. Dremio’s Agentic Lakehouse autonomously manages itself, removing undifferentiated management tasks, allowing engineers to focus on initiatives that drive business results. Dremio’s agentic lakehouse automatically optimizes queries, reorganizes data, and maintains performance at any scale. Dremio is trusted by thousands of global enterprises including Shell, TD Bank, and Michelin, and built on open standards. Dremio co-created Apache Polaris and Apache Arrow, and it's the only lakehouse built natively on Apache Iceberg, Polaris, and Arrow.

Average Rating: 4.6/5.0

Total Reviews: 65

How Do G2 Users Rate Dremio?

  • Ease of Use: 9.2/10 (Category avg: 8.7/10)
  • Data Governance: 8.2/10 (Category avg: 8.4/10)
  • Scalability: 8.3/10 (Category avg: 8.5/10)

Who Is the Company Behind Dremio?

  • Seller: Dremio
  • Year Founded: 2015
  • HQ Location: Santa Clara, California
  • Twitter: @dremio
    5,112 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    357 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Financial Services, Information Technology and Services
  • Company Size: 49% Large, 39% Medium

What Do G2 Reviewers Say About Dremio?

AI-generated summary from verified user reviews

Pros
  • Users find Dremio to be stupidly easy to use, enhancing efficiency in data sharing and visualization.
  • Users value Dremio's seamless integrations with tools like Power BI and Tableau for efficient data management.
  • Users commend Dremio for its impressive performance, accelerating queries and simplifying data collection across multiple sources.
  • Users value the SQL support in Dremio, facilitating seamless data integration and efficient analysis across platforms.
  • Users highlight Dremio's exceptional data management capabilities, simplifying data manipulation and enhancing analytics for informed decisions.
Cons
  • Users find the initial setup complicated and note a steep learning curve for effective implementation of Dremio.
  • Users note that customer support can be slow, occasionally leading to delays in resolving issues and assisting users.
  • Users find the learning curve steep, making it challenging to fully adopt and utilize Dremio effectively.
  • Users find the difficult setup of Dremio to be a time-consuming challenge, hindering their overall experience.
  • Users often find poor documentation frustrating, relying on forums instead of clear resources for configuration details.

What Are Recent G2 Reviews of Dremio?

What Are G2 Users Discussing About Dremio?

ILUM

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

How Do G2 Users Rate ILUM?

  • Ease of Use: 9.3/10 (Category avg: 8.7/10)
  • Data Governance: 9.3/10 (Category avg: 8.4/10)
  • Data Security: 9.2/10 (Category avg: 8.8/10)
  • Scalability: 9.5/10 (Category avg: 8.5/10)

Who Is the Company Behind ILUM?

  • Seller: Ilum
  • Company Website:
  • Year Founded: 2019
  • HQ Location: Santa Fe, US
  • Twitter: @IlumCloud
    19 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    5 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Telecommunications
  • Company Size: 52% Large, 35% Medium

What Do G2 Reviewers Say About ILUM?

AI-generated summary from verified user reviews

Pros
  • Users praise ILUM for its ease of use, with a clean UI and quick deployment enhancing productivity and workflow.
  • Users praise ILUM for its seamless integration, user-friendly interface, and excellent customer support, streamlining data management effectively.
  • Users value the seamless integrations of ILUM, enhancing productivity by connecting various systems and streamlining workflows.
  • Users love the ease of setup with ILUM, noting quick deployments and user-friendly interfaces that enhance productivity.
  • Users value the easy integrations of ILUM, enhancing their data workflows and simplifying complex processes effortlessly.
Cons
  • Users note that the complex setup of ILUM can be challenging, requiring time and effort to configure properly.
  • Users note the difficult setup of ILUM, requiring experimentation and digging for advanced configurations and integrations.
  • Users note the steep learning curve for new users, though intuitive daily use improves after initial setup.
  • Users note that the UX could be improved with more intuitive navigation and clearer configuration options.
  • Users find ILUM's complexity in advanced configurations may require time and effort to fully navigate and optimize.

What Are Recent G2 Reviews of ILUM?

EXASOL

Exasol is the world’s ​most powerful Analytics Engine, ​purpose-built to handle the most demanding data workloads at an unmatched price / performance ratio​. In-memory architecture Want to process 3 billion rows in 3 seconds, not 3 hours? Exasol manages memory cache automatically, only bringing what's needed into the database for dramatically faster access times. Automatic query tuning Enjoy optimized performance while minimizing data administration overhead. Exasol uses intelligent, proprietary algorithms to self-tune queries on the fly -- adding and removing indices automatically – so you can bring true self-service BI to your organization. User defined functions (UDF) When you need more than a SQL statement, UDF scripts allow you to program your own analysis. Take your unique machine learning and data ingest scripts written in Python, R, and Lua, and run them in our database engine. Through UDF scripts, you'll get a highly flexible interface for nearly every requirement, allowing you to bring in data quickly from wherever it lives. In addition to being the fastest, Exasol also leads in the TPC price-performance metrics, meaning everyone in your organization can take advantage of unrivaled in-memory speed at a low price. And, unlike our competitors, Exasol allows you to choose the deployment destination. Deploy in the cloud, on-premises, or hybrid to meet your organization's unique needs and preferred vendors.

Average Rating: 4.7/5.0

Total Reviews: 23

How Do G2 Users Rate EXASOL?

  • Ease of Use: 9.0/10 (Category avg: 8.7/10)
  • Data Governance: 9.7/10 (Category avg: 8.4/10)
  • Data Security: 8.6/10 (Category avg: 8.8/10)
  • Scalability: 10.0/10 (Category avg: 8.5/10)

Who Is the Company Behind EXASOL?

  • Seller: EXASOL
  • Year Founded: 2000
  • HQ Location: Nurnberg, Bayern
  • LinkedIn® Page: www.linkedin.com
    220 employees on LinkedIn®

Who Uses This Product?

  • Company Size: 39% Large, 32% Medium

What Do G2 Reviewers Say About EXASOL?

AI-generated summary from verified user reviews

Pros
  • Users highlight the unmatched query performance of EXASOL, enabling incredibly fast results for large data sets.
  • Users highlight the unparalleled query performance of EXASOL, achieving rapid results even with massive data sets.
  • Users value the unparalleled query performance of EXASOL, enhancing efficiency for analytical workloads with speed and reliability.
  • Users find EXASOL to be cost-effective, appreciating its efficiency and minimal administrative requirements.
  • Users appreciate the fast and competent customer support from EXASOL, enhancing their overall experience with the product.
Cons
  • Users experience complexity in query optimization, which can hinder performance despite available tricks for improvement.
  • Users report challenges with the lack of a robust debugger in EXASOL, making Python code development difficult.
  • Users find the difficult setup of EXASOL requires extensive configuration and DBA involvement for upgrades.
  • Users find the limited visualization capabilities of EXASOL hinder their ability to analyze data effectively.
  • Users experience performance issues with Exasol's optimizer, impacting complex query execution but workaround solutions are available.

What Are Recent G2 Reviews of EXASOL?

What Are G2 Users Discussing About EXASOL?

SAP Business Data Cloud

SAP Business Data Cloud is a fully managed software-as-a-service (SaaS) solution that unifies and governs SAP data and connects with third-party data. As an evolution of the company's data, planning, and analytics solutions, SAP Business Data Cloud brings together SAP Datasphere, SAP Analytics Cloud, and SAP Business Warehouse with a unified experience that delivers insights across all lines of business. In addition, SAP Databricks is natively available in Business Data Cloud - bringing the power of Databricks Data Intelligence Platform capabilities to the product. SAP Business Data Cloud connects data by leveraging business data fabric principles, making it easier to discover, share, govern, and model this data. It includes SAP Databricks as a first-party data service. The platform combines prebuilt applications and data products across all lines of business. It provides fully managed, curated data products across all lines of business and eliminate the costs of data extracts. Users can build on SAP’s curated data products with their domain expertise, and deliver Intelligent Applications through the Business Data Cloud ecosystem. These intelligent applications are adaptive, AI-powered applications that learn from your data, understand business context, and act on your behalf to transform business outcomes.

Average Rating: 4.2/5.0

Total Reviews: 74

How Do G2 Users Rate SAP Business Data Cloud?

  • Ease of Use: 8.1/10 (Category avg: 8.7/10)

Who Is the Company Behind SAP Business Data Cloud?

  • Seller: SAP
  • Company Website:
  • Year Founded: 1972
  • HQ Location: Walldorf
  • Twitter: @SAP
    297,052 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    149,349 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 39% Large, 29% Small

What Do G2 Reviewers Say About SAP Business Data Cloud?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of SAP Business Data Cloud, facilitating seamless data integration and smoother workflows.
  • Users value the business-ready semantic layer of SAP Business Data Cloud for its real-time, actionable data access.
  • Users value the seamless data integration capabilities of SAP Business Data Cloud for efficient data management and insights.
  • Users value the single, trusted view of data provided by SAP Business Data Cloud, streamlining daily operations effectively.
  • Users value the seamless data integration of SAP Business Data Cloud, enabling unified data access for enhanced decision-making.
Cons
  • Users find the complex setup process of SAP Business Data Cloud challenging, particularly in hybrid environments.
  • Users find that integration issues make setup complex and challenging, particularly in hybrid environments.
  • Users experience a difficult learning curve due to the complexity of advanced options and integration requirements.
  • Users highlight the high cost of SAP Business Data Cloud, which complicates budget management and may deter smaller organizations.
  • Users note a steep learning curve with SAP Business Data Cloud, making it challenging for beginners to utilize effectively.

What Are Recent G2 Reviews of SAP Business Data Cloud?

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: 4.4/5.0

Total Reviews: 106

How Do G2 Users Rate Starburst?

  • Ease of Use: 8.9/10 (Category avg: 8.7/10)
  • Data Governance: 7.7/10 (Category avg: 8.4/10)
  • Data Security: 8.4/10 (Category avg: 8.8/10)
  • Scalability: 8.9/10 (Category avg: 8.5/10)

Who Is the Company Behind Starburst?

  • Seller: Starburst
  • Company Website:
  • Year Founded: 2017
  • HQ Location: Boston, MA
  • Twitter: @starburstdata
    3,454 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    543 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Information Technology and Services, Financial Services
  • Company Size: 43% Large, 34% Small

What Do G2 Reviewers Say About Starburst?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the fast querying capabilities of Starburst, significantly enhancing their data analysis efficiency across diverse sources.
  • Users commend Starburst for its exceptional query efficiency, enabling seamless execution of complex queries across multiple data sources.
  • Users are impressed by the fast and efficient data querying that Starburst offers, simplifying complex analytics tasks.
  • Users find Starburst's ease of use impressive, highlighting quick setup and maintenance-free administration.
  • Users value the seamless integration with various data sources, significantly enhancing data access and analysis efficiency.
Cons
  • Users face query issues with performance delays, particularly with complex or large datasets impacting efficiency and insights.
  • Users experience slow performance on Starburst, especially with complex queries and multiple simultaneous users affecting efficiency.
  • Users note the poor documentation that lacks advanced examples, making it hard for enterprise-level needs.
  • Users find the setup and complexity of Starburst challenging, especially for beginners navigating its advanced features.
  • Users often experience performance issues with Starburst, especially when handling large data sets and complex queries.

What Are Recent G2 Reviews of Starburst?

What Are G2 Users Discussing About Starburst?

Rocket Vertica

Vertica é a plataforma de análise unificada, baseada em uma arquitetura massivamente escalável com um amplo conjunto de funções analíticas que abrangem eventos e séries temporais, correspondência de padrões, geoespacial e capacidade de aprendizado de máquina embutida. Vertica permite que as equipes de análise de dados apliquem facilmente essas funções poderosas a cargas de trabalho analíticas grandes e exigentes, armando-as e a seus clientes com insights de negócios preditivos. Vertica fornece uma plataforma de análise unificada em grandes nuvens públicas e data centers locais, e integra dados em armazenamento de objetos na nuvem e HDFS sem forçar qualquer movimentação de dados. Disponível como uma opção SaaS, ou como uma plataforma gerida pelo cliente, Vertica ajuda as equipes a combinar silos de dados em crescimento para uma visão mais completa dos dados disponíveis. Vertica apresenta separação de computação e armazenamento, para que as equipes possam ativar recursos de armazenamento e computação conforme necessário, e depois desativá-los para reduzir custos.

Average Rating: 4.3/5.0

Total Reviews: 195

How Do G2 Users Rate Rocket Vertica?

  • Facilidade de Uso: 8.5/10 (Category avg: 8.7/10)
  • Governança de dados: 8.3/10 (Category avg: 8.4/10)
  • Segurança de dados: 8.5/10 (Category avg: 8.8/10)
  • Escalabilidade: 8.3/10 (Category avg: 8.5/10)

Who Is the Company Behind Rocket Vertica?

  • Vendedor: Rocket Software
  • Ano de Fundação: 1990
  • Localização da Sede: Waltham, MA
  • Twitter: @Rocket
    3,532 seguidores no Twitter
  • Página do LinkedIn®: www.linkedin.com
    4,417 funcionários no LinkedIn®

Who Uses This Product?

  • Who Uses This: Engenheiro de Software Sênior, Engenheiro de Dados
  • Top Industries: Software de Computador, Tecnologia da Informação e Serviços
  • Company Size: 44% Large, 39% Medium

What Are Recent G2 Reviews of Rocket Vertica?

What Are G2 Users Discussing About Rocket Vertica?

Panoply

A Panoply facilita a sincronização, armazenamento e acesso aos seus dados de qualquer fonte de dados. A solução fácil de usar e de baixa manutenção da Panoply desbloqueia análises sofisticadas sem engenharia de dados complexa e codificação: Os principais recursos da plataforma Panoply incluem: - Integrações de dados sem código para sincronização perfeita - Configuração automatizada de data warehouse - Uma poderosa bancada de trabalho para exploração e visualização de dados baseados em SQL - Dashboards e relatórios na plataforma - Conexões com todas as principais ferramentas de BI e analíticas - Onboarding e suporte líderes do setor

Average Rating: 4.5/5.0

Total Reviews: 80

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How Do G2 Users Rate Panoply?

  • Facilidade de Uso: 8.9/10 (Category avg: 8.7/10)
  • Governança de dados: 7.8/10 (Category avg: 8.4/10)
  • Segurança de dados: 8.7/10 (Category avg: 8.8/10)
  • Escalabilidade: 8.1/10 (Category avg: 8.5/10)

Who Is the Company Behind Panoply?

  • Vendedor: Panoply
  • Ano de Fundação: 2015
  • Localização da Sede: San Francisco, CA
  • Twitter: @panoplyio
    5,485 seguidores no Twitter
  • Página do LinkedIn®: www.linkedin.com
    13 funcionários no LinkedIn®

Who Uses This Product?

  • Top Industries: Tecnologia da Informação e Serviços, Software de Computador
  • Company Size: 47% Small, 43% Medium

What Do G2 Reviewers Say About Panoply?

AI-generated summary from verified user reviews

Pros
  • Os usuários elogiam o atendimento ao cliente prestativo e responsivo da Panoply, facilitando a resolução de problemas e orientação sem complicações.
  • Os usuários apreciam a facilidade de uso do Panoply, elogiando o suporte responsivo da equipe para resolução de problemas e configuração.
  • Os usuários valorizam as integrações úteis do Panoply, recebendo assistência rápida com a configuração e solução de problemas.
Cons
  • Os usuários desejam os recursos de revisão de código na bancada de trabalho do Panoply, semelhantes aos do portal do Big Query.

What Are Recent G2 Reviews of Panoply?

What Are G2 Users Discussing About Panoply?