Best Enterprise Data Warehouse Solutions - Page 2

How Many Data Warehouse Solutions Products Does G2 Track?

Total Products under this Category: 131

Category Stats (Oct 2026)

  • Average Rating: 4.38/5 (↑0.01 vs Sep 2026) The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: Sesame Software (+0.35%) - Among all products in this category, Sesame Software recorded the largest rating increase compared to last month

Last updated: October 15, 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
  • 131+ 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, Teradata Autonomous Knowledge Platform, Amazon Redshift, VMware Greenplum, and IBM watsonx.data.

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=teradata-autonomous-knowledge-platform&focus%5B%5D=amazon-redshift&focus%5B%5D=vmware-greenplum&focus%5B%5D=ibm-watsonx-data&segment=enterprise)

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: 75

How Do G2 Users Rate SAP Business Data Cloud?

  • Ease of Use: 8.1/10 (Category avg: 8.8/10)

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: 40% 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 experience a difficult learning curve due to the complexity of advanced options and integration requirements.
  • Users find that integration issues make setup complex and challenging, particularly in hybrid environments.
  • 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?

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: 193

How Do G2 Users Rate Cloudera?

  • Ease of Use: 8.3/10 (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: 9.3/10 (Category avg: 8.5/10)

Who Is the Company Behind Cloudera?

  • Seller: Cloudera
  • Company Website:
  • Year Founded: 2008
  • HQ Location: Santa Clara, CA
  • Twitter: @cloudera
    106,442 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    3,505 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Software Engineer
  • Top Industries: Information Technology and Services, Banking
  • Company Size: 37% Large, 34% Small

What Do G2 Reviewers Say About Cloudera?

AI-generated summary from verified user reviews

Pros
  • Users praise the user-friendly interface of Cloudera, highlighting its simplicity in managing big data efficiently.
  • Users value the easy scalability of Cloudera, enabling efficient management of large amounts of data effortlessly.
  • Users value the robust security features of Cloudera, ensuring safe and reliable data management across platforms.
  • Users value the comprehensive suite of tools in Cloudera for effective data management and analytics.
  • Users find Cloudera's scalability and centralized administration invaluable for efficient monitoring and management of data processes.
Cons
  • Users express concerns over the high costs of Cloudera, noting it's expensive for its complexity and maintenance.
  • Users find Cloudera's database to be complex, making it challenging for inexperienced professionals to utilize effectively.
  • Users find Cloudera's setup difficult to learn, particularly challenging for beginners without adequate tutorials or guidance.
  • Users find the poor documentation of Cloudera frustrating, complicating navigation and setup for complex data configurations.
  • Users often face access issues with Cloudera, particularly with unauthorized errors in Airflow tasks and limited documentation.

What Are Recent G2 Reviews of Cloudera?

What Are G2 Users Discussing About Cloudera?

Oracle Exadata Cloud Service

Offer a fast, reliable, and cost-effective platform for data warehousing and business intelligence that is easy to scale to meet the complex reporting.

Average Rating: 4.4/5.0

Total Reviews: 40

How Do G2 Users Rate Oracle Exadata Cloud Service?

  • Ease of Use: 7.7/10 (Category avg: 8.8/10)
  • Data Governance: 9.0/10 (Category avg: 8.4/10)
  • Data Security: 9.0/10 (Category avg: 8.8/10)
  • Scalability: 9.2/10 (Category avg: 8.5/10)

Who Is the Company Behind Oracle Exadata Cloud Service?

  • Seller: Oracle
  • Year Founded: 1977
  • HQ Location: Austin, TX
  • Twitter: @Oracle
    827,997 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    207,576 employees on LinkedIn®
  • Ownership: NYSE:ORCL

Who Uses This Product?

  • Top Industries: Banking, Government Administration
  • Company Size: 73% Large, 23% Medium

What Are Recent G2 Reviews of Oracle Exadata Cloud Service?

What Are G2 Users Discussing About Oracle Exadata Cloud Service?

AI can help you find the answers. G2 helps you trust them.

Connect G2 to Claude or ChatGPT for answers grounded in G2's trusted reviews, comparisons, and pricing from real user insights.

How it works
Connect G2 to ChatGPTConnect G2 to Claude

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?

  • Seller: Rocket Software
  • Year Founded: 1990
  • HQ Location: Waltham, MA
  • Twitter: @Rocket
    3,532 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    4,417 employees on LinkedIn®

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?

IBM InfoSphere Information Server

Better understand your data and cleanse, monitor, transform and deliver it. Build confidence in your data Delivers clean, consistent and timely information for your data warehouses or big data projects and applications. Create a flexible governance strategy Helps you adapt a data governance strategy to suit your organizational objectives, while shaping business information in unique ways to meet your needs. Modernize and consolidate your systems Enables you to consolidate applications, retire outdated databases and modernize your infrastructure, as well as automate business processes for improved cost savings. Connect business and IT Provides a unified platform that enables collaboration, which can help you bridge the gap between business and IT and align objectives.

Average Rating: 4.1/5.0

Total Reviews: 22

How Do G2 Users Rate IBM InfoSphere Information Server?

  • Ease of Use: 7.2/10 (Category avg: 8.8/10)
  • Data Governance: 8.3/10 (Category avg: 8.4/10)
  • Data Security: 8.3/10 (Category avg: 8.8/10)
  • Scalability: 8.3/10 (Category avg: 8.5/10)

Who Is the Company Behind IBM InfoSphere Information Server?

  • 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?

  • Top Industries: Financial Services, Information Technology and Services
  • Company Size: 96% Large, 26% Medium

What Are Recent G2 Reviews of IBM InfoSphere Information Server?

What Are G2 Users Discussing About IBM InfoSphere Information Server?

Yellowbrick

Yellowbrick is a high-performance, cloud-native data platform designed for hybrid multi-cloud and on-premises environments. It supports a wide variety of workloads, including traditional data warehousing, real-time streaming analytics, application analytics, and AI/ML workloads. Yellowbrick's architecture leverages the power of Kubernetes to deliver scalability, elasticity, and operational simplicity through SQL or a web interface, abstracting any user Kubernetes management. It provides unmatched speed and efficiency in SQL analytics, powered by the Direct Data Accelerator® and supports simultaneous querying and data loading with no impact on performance.

Average Rating: 4.9/5.0

Total Reviews: 14

How Do G2 Users Rate Yellowbrick?

  • Ease of Use: 9.4/10 (Category avg: 8.8/10)
  • Data Governance: 9.4/10 (Category avg: 8.4/10)
  • Data Security: 9.4/10 (Category avg: 8.8/10)
  • Scalability: 8.3/10 (Category avg: 8.5/10)

Who Is the Company Behind Yellowbrick?

  • Seller: Yellowbrick Data
  • Year Founded: 2014
  • HQ Location: Mountain View, US
  • Twitter: @YellowbrickData
    6,853 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    82 employees on LinkedIn®

Who Uses This Product?

  • Company Size: 71% Large, 29% Medium

What Are Recent G2 Reviews of Yellowbrick?

What Are G2 Users Discussing About Yellowbrick?

SAP BW/4HANA

SAP BW/4HANA is a next-generation data warehouse solution. It is specifically designed to use the advanced in-memory capabilities of the SAP HANA platform. For example, SAP BW/HANA can integrate many different data sources to provide a single, logical view of all the data. This could include data contained in SAP and non-SAP applications running on-premise or in the cloud, and data lakes, such as those contained in the Apache Hadoop open-source software framework. With SAP BW/4HANA, IT organizations can become the hero, providing business users with real-time analytics, tailored analytical applications, and intelligent automated support for business processes based on data from SAP and non-SAP line-of-business applications.

Average Rating: 4.0/5.0

Total Reviews: 15

How Do G2 Users Rate SAP BW/4HANA?

  • Ease of Use: 7.9/10 (Category avg: 8.8/10)
  • Data Governance: 8.3/10 (Category avg: 8.4/10)
  • Data Security: 8.3/10 (Category avg: 8.8/10)
  • Scalability: 10.0/10 (Category avg: 8.5/10)

Who Is the Company Behind SAP BW/4HANA?

  • 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?

  • Company Size: 68% Large, 16% Medium

What Are Recent G2 Reviews of SAP BW/4HANA?

Zap Data Hub

Zap Data Hub is a data warehouse automation solution that streamlines the extraction, loading and transformation (ELT) of ERP and business data into a centralized, governed warehouse for reporting and analytics. Zap Data Hub is used by finance, operations and IT teams who need a faster, more structured way to integrate ERP data from platforms such as Microsoft Dynamics 365, SAP Business One, Sage and SYSPRO alongside other business sources like CRM, payroll and inventory systems. It automates the heavy lifting involved in data integration and preparation, allowing businesses to build a trusted data foundation without extensive coding or manual processes. By automatically mapping, transforming and loading data into a warehouse, Zap eliminates reliance on spreadsheets, manual extracts and disconnected reporting. It creates a governed semantic model that ensures consistent metrics across tools like the Power BI integration, Excel add-in and browser-based reporting. Zap can be deployed in the cloud or on-premises, with support for Microsoft Fabric. Key features and value points • End-to-end data warehouse automation that structures and governs data from ERP and other business systems • Pre-built ERP connectors and models that accelerate deployment and reduce implementation effort • Governed semantic model that ensures consistent, trusted reporting across business units and analytics tools • Reporting support through the Excel add-in, Power BI integration and browser-based options • Deployment flexibility offering cloud-based or on-premises options • Future-ready architecture that integrates with Microsoft Fabric and supports evolving analytics needs Zap Data Hub is suited to organizations that want to automate their reporting data foundations, improve governance and drive business insights without the complexity of manual data engineering.

Average Rating: 4.3/5.0

Total Reviews: 44

How Do G2 Users Rate Zap Data Hub?

  • Ease of Use: 8.0/10 (Category avg: 8.8/10)
  • Data Governance: 7.6/10 (Category avg: 8.4/10)
  • Data Security: 7.7/10 (Category avg: 8.8/10)
  • Scalability: 8.3/10 (Category avg: 8.5/10)

Who Is the Company Behind Zap Data Hub?

  • Seller: ZAP
  • Year Founded: 2001
  • HQ Location: Brisbane, Australia
  • Twitter: @ZAP_Data
    1,552 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    87 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Oil & Energy, Computer Software
  • Company Size: 61% Medium, 28% Large

What Do G2 Reviewers Say About Zap Data Hub?

AI-generated summary from verified user reviews

Pros
  • Users praise the ease of use of Zap Data Hub, emphasizing effortless data integration and real-time access.
  • Users value the easy data integration with Zap Data Hub, simplifying ETL processes and enhancing operational efficiency.
  • Users appreciate the excellent customer support from the Zap Team, enhancing their overall experience and satisfaction.
  • Users value the clean reporting functionality of Zap Data Hub, appreciating its seamless integration and time-saving capabilities.
  • Users appreciate the robust analytics capabilities of Zap Data Hub, enabling seamless data integration and BI reporting.
Cons
  • Users find the steep learning curve of Zap Data Hub challenging, requiring support for comfortable usage and report development.
  • Users face complexity challenges when connecting to live Excel data and performing certain calculations effectively.
  • Users face challenges with importing Excel data, particularly with live connections and large file management.
  • Users face challenges with connecting to Excel sources and report exports, affecting overall usability of Zap Data Hub.
  • Users note a steep learning curve, making it challenging for occasional users to navigate and utilize effectively.

What Are Recent G2 Reviews of Zap Data Hub?

Hive

Hive provides a mechanism to project structure onto this data and query the data using a SQL-like language called HiveQL. At the same time this language also allows traditional map/reduce programmers to plug in their custom mappers and reducers when it is inconvenient or inefficient to express this logic in HiveQL.

Average Rating: 4.2/5.0

Total Reviews: 57

How Do G2 Users Rate Hive?

  • Ease of Use: 8.4/10 (Category avg: 8.8/10)
  • Data Governance: 9.0/10 (Category avg: 8.4/10)
  • Data Security: 8.8/10 (Category avg: 8.8/10)
  • Scalability: 7.9/10 (Category avg: 8.5/10)

Who Is the Company Behind Hive?

Who Uses This Product?

  • Who Uses This: Data Engineer
  • Top Industries: Computer Software, Internet
  • Company Size: 55% Large, 35% Medium

What Are Recent G2 Reviews of Hive?

What Are G2 Users Discussing About Hive?

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

Reviews Summary: The Best Data Warehouse Software for Enterprise Businesses

Thanks to 7124 Data Warehouse software reviews and associated data from users working for large-scale companies, at G2 we have some of the most definitive data on the best Data Warehouse software for the large space. We have identified 24 individual Data Warehouse products offering the features, pricing and support that Enterprise 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 large-scale 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)
  • large Data Warehouse Software Reviews (51-1,000 employees)
  • Enterprise Data Warehouse Software Reviews (1,001+ employees)

large businesses have their own unique requirements when it comes to Data Warehouse software compared to small or enterprise companies. That is why these individual large-scale 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 large environments. These reviews are written by real G2 users working for these Enterprise companies who have real-world experience with these Data Warehouse software products.

FAQs About Data Warehouse Software for Enterprise Businesses

Q. What are the best Data Warehouse software products for large-scale businesses, according to G2 reviewers?
  • Databricks - 4.7-stars, 246 reviews (48% from large reviewers)
  • Google Cloud BigQuery - 4.5-stars, 249 reviews (38% from large reviewers)
  • Snowflake - 4.5-stars, 264 reviews (42% from large reviewers)
  • SAP Datasphere - 4.2-stars, 63 reviews (41% from large reviewers)
  • VMware Greenplum - 4.2-stars, 26 reviews (47% from large reviewers)
Q. What are the least-liked Data Warehouse software products for professionals at large-scale companies, based on the overall G2 rating?
  • Hive - 4.1-stars, 31 reviews (54% from large reviewers)
  • Zap Data Hub - 3.8-stars, 12 reviews (28% from large reviewers)
  • SAP BW/4HANA - 4.0-stars, 11 reviews (73% from large reviewers)
  • Yellowbrick - 4.9-stars, 10 reviews (71% from large reviewers)
  • IBM InfoSphere Information Server - 4.2-stars, 10 reviews (91% from large reviewers)
Q. What are the highest-rated Data Warehouse software tool features according to employees at Enterprise companies?
  • Scalability - 4.4-stars
  • Data Security - 4.4-stars
  • Cloud - 4.4-stars
Q. What are the features that are rated lowest by employees at Enterprise companies?
  • AI Text Summarization - 3.6-stars
  • AI Text Generation - 3.7-stars
  • In-Database Machine Learning - 3.9-stars
Q. How many Data Warehouse software reviews are from users working in large companies?

1660 out of all Data Warehouse software reviews on G2 are from users working in Enterprise companies (23%).

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

What Enterprise Professionals Liked What Enterprise Professionals Disliked

Databricks: “Databricks is especially helpful because it brings data engineering, analytics, and machine learning together in a single unified platform, which reduces the need to manage multiple separate tools. Built on Apache Spark, it can process massive datasets quickly and scale smoothly as workloads grow, making it a strong fit for big data use cases. It also supports collaborative notebooks where teams can work together in languages like Python and SQL, which makes it easier for data scientists and engineers to collaborate effectively. With its lakehouse architecture powered by Delta Lake, Databricks combines the flexibility of data lakes with the reliability of data warehouses, helping ensure better data consistency and performance. In addition, it integrates with tools like MLflow to streamline the machine learning lifecycle end to end, from experimentation through deployment. Overall, Databricks simplifies complex data workflows, improves performance, and helps organizations build scalable data and AI solutions more efficiently.”

Read Review

IBM Db2: “You can't declare global variables, after using more than 5 different databases this is the first I've come across that does not support them. There is no online support or documentation that can give you the answer you are looking for. It does not support PIVOT/UNPIVOT functions so you are not able to transpose anything. This system was big in the '80s and died in the '80s. After showing clients who use DB2 a different database system (literally any, didn't matter which really) they were blown away and instantly started transitioning away from DB2 and on to the new system.”

Read Review

Databricks: “Unity Catalog has been the single biggest value-add for our enterprise migration. We moved from a Hive Metastore architecture to Unity Catalog and gained centralized governance, lineage tracking, and fine-grained access control across all our data assets without bolting on third-party tools. For a multi-domain organization (finance, manufacturing, supply chain, procurement), having one catalog that enforces consistent naming and permissions across bronze, silver, gold, and platinum layers saved us weeks of manual policy work. UI/UX: The notebook experience with inline Spark SQL and PySpark, combined with the workspace file browser, makes it straightforward for our team to develop and test transformations iteratively. The SQL editor for ad-hoc queries against Unity Catalog tables is clean and responsive. Integrations: Native Delta Lake support means we don't manage format conversions. The Azure Key Vault integration via secret scopes (dbutils.secrets.get) keeps credentials out of code. ADF integration for orchestration in our V1 environment was seamless, and Databricks Asset Bundles (DAB) for V2 deployment give us a clean CI/CD path with databricks.yml configs targeting dev/qa/prod without custom scripting. Performance: Switching to CTEs over temp views in our Gold notebooks reduced cluster memory pressure noticeably. The ability to right-size clusters per environment (1 worker for dev, 3 for production) with Standard_D4ds_v5 nodes keeps costs predictable while maintaining performance for our batch ETL workloads. Pricing/ROI: The pay-as-you-go compute model paired with single-user security mode clusters means we're not over-provisioning. Consolidating our ETL, governance, and BI serving layer into one platform eliminated licensing for separate catalog, orchestration, and data quality tools. AI/Intelligence (Genie): Genie Spaces have been an unexpected win. Our business analysts in finance and supply chain can ask natural language questions against curated Gold/Platinum tables without writing SQL. It reduced the number of ad-hoc report requests coming to the data team by giving domain users a self-service path that still respects Unity Catalog permissions. Support/Onboarding: The documentation is thorough, and the skills-based approach to learning (bundles, Unity Catalog, jobs, SQL) maps well to how our team actually works. Onboarding new engineers to the V2 architecture took about half the time compared to V1 because the platform conventions (medallion architecture, asset bundles, catalog naming) are well-documented and consistent.”

Read Review

SAP Datasphere: “The existing version of S4 does not allow for good connectors. Data replication is not reliable and can take up to 24 hours.”

Read Review

Databricks: “This is really a nice user friendly platform.”

Read Review

Hive: “. at my company it was fairly troublesome getting access since it's underlying warehouseing is in hadoop, then have to connect through hive”

Read Review
Recommendations To Others Problems Solved & Benefits

Rocket Vertica: “It is best tool for data warehousing and solving Big Data solutions. Also, It provides fastest ETL transactions and on-time data delivery.”

Read Review

Cloudera: “We help implement Cloudera for data warehouse migration and modernization, big data initiatives, and Generative AI initiatives. For data warehouse modernization and big data initiatives, our customers benefit from a modern data lakehouse stack, improved performance, and reduced data silos by creating a single source of truth on top of Cloudera. With Cloudera data services, our customers can explore data faster and run ad-hoc reports more easily, powered by Cloudera Data Explorer and Impala on top of virtual warehouses. Cloudera AI also helps our customers get started with their Generative AI use cases, enabling them to quickly create LLM-powered apps without needing to manually set up infrastructure and security.”

Read Review

Google Cloud BigQuery: “Help needed in developing complex OLTP data models”

Read Review

Cloudera: “We are under implementation phase”

Read Review

Snowflake: “Dig in and play around. Use the built in geospatial functions.”

Read Review

Cloudera: “Big Data Lake, CML”

Read Review