# Best Enterprise Data Warehouse Solutions

## How Many Data Warehouse Solutions Products Does G2 Track?

**Total Products under this Category:** 120

### Category Stats (Jul 2026)

- **Average Rating:** 4.37/5 The average rating of products in this category, based on all submitted ratings
- **Top Trending Product:** Rubrik (+0.2%) - Among all products in this category, Rubrik recorded the largest rating increase compared to last month

_Last updated: July 31, 2026_

## How Does G2 Rank Data Warehouse Solutions Products?

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

- 30 Analysts and Data Experts
- 7,400+ Authentic Reviews
- 120+ 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](https://www.g2.com/categories/data-warehouse/grids.png?focus%5B%5D=10470&focus%5B%5D=6073&focus%5B%5D=10938&focus%5B%5D=129730&focus%5B%5D=6058&focus%5B%5D=10898&focus%5B%5D=58132&focus%5B%5D=1308796)

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)

**Sponsored**

### 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.

[Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list_llm&secure%5Bcategory_id%5D=77&secure%5Bchosen_at%5D=2026-07-31T22%3A27%3A12Z&secure%5Bdisplayable_resource_id%5D=77&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=77&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=6073&secure%5Bresource_id%5D=77&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fdata-warehouse%2Fenterprise%3Fopen_modal_url%3D%252Fproducts%252Fopentext-vertica%252Fwishlists%253Fhost_path%253D%25252Fcategories%25252Fdata-warehouse%25252Fenterprise%2526source%253Dcategory&secure%5Btoken%5D=16d9731a895acc544afcb06895dd036b18a1da0c4dc9dedcb169984564647058&secure%5Burl%5D=https%3A%2F%2Fcloud.google.com%2Fbigquery%3Futm_source%3DG2%26utm_medium%3Ddisplay%26utm_campaign%3DCloud-SS-DR-GCP-1713658-GCP-DR-NA-US-en-G2-Display-Banner-All-%2525epid%21-%2525ecid%21-bigquery%26utm_content%3D%257Bdevice%257D-%257Badgroupid%257D-%257Bnetwork%257D-%257Btargetid%257D-%257Bloc_physical_ms%257D-%257Bcampaignid%257D&secure%5Burl_type%5D=custom_url)

### [Databricks](https://www.g2.com/products/databricks/reviews)

Databricks is a unified data and AI platform that helps organizations build, govern and scale data pipelines, analytics, machine learning, AI applications and agents. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on Databricks to work with enterprise data and AI at scale. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Agent Bricks, Lakeflow, Lakehouse, Lakebase, Genie 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:** 1,326

#### 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:** 9.0/10 (Category avg: 8.8/10)
- **Scalability:** 9.2/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Databricks?

- **Seller:** [Databricks Inc.](https://www.g2.com/sellers/databricks-inc)
- **Company Website:** databricks.com
- **Year Founded:** 2013
- **HQ Location:** San Francisco, CA
- **Twitter:** @databricks  
92,269 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=bddca64732f61b923d96364e8c8eb35711aab4f98797cb00ab071ff24fbdd392&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F3477522%2F&secure%5Burl_type%5D=linkedin_company_website)  
15,627 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 praise the **ease of use** and **comprehensive features** of Databricks for data warehousing and ML applications.
- Users praise the **ease of use** of Databricks, enhancing their experience with intuitive interfaces and reliable services.
- Users appreciate the **seamless integrations** of Databricks with AWS and other tools, enhancing daily operations and efficiency.
- Users value the **seamless collaboration** offered by Databricks, enhancing teamwork on data projects with real-time insights.
- Users praise the **integrated analytical features** of Databricks, enhancing collaborative data processing and insight visualization.

##### Cons

- Users note a **steep learning curve** initially, with confusing permissions and compute modes affecting usability.
- Users note that the **costs can be quite high** for utilizing Databricks effectively, especially for large data projects.
- Users find a **steep learning curve** with Databricks, especially challenging for newcomers to big data tools.
- Users find the **complexity** of Databricks challenging, especially for smaller teams and initial setup processes.
- Users face **complex setup** challenges initially, though support helps simplify the experience over time.

#### What Are Recent G2 Reviews of Databricks?

**["Databricks Streamlines ETL and Analytics with Scalable Notebooks"](https://www.g2.com/survey_responses/databricks-review-13181721)**

**Rating:** 5.0/5.0 stars

_— Diana C._

[Read full review](https://www.g2.com/survey_responses/databricks-review-13181721)

**["Helpful for Managing and Analyzing Operational Data"](https://www.g2.com/survey_responses/databricks-review-13090803)**

**Rating:** 4.5/5.0 stars

_— Vishaka C._

[Read full review](https://www.g2.com/survey_responses/databricks-review-13090803)

#### What Are G2 Users Discussing About Databricks?

- [What does Databricks software do?](https://www.g2.com/discussions/what-does-databricks-software-do) - 3 comments, 1 upvote
- [What is Databricks unified analytics platform?](https://www.g2.com/discussions/what-is-databricks-unified-analytics-platform) - 3 comments
- [What is Lakehouse in Databricks?](https://www.g2.com/discussions/what-is-lakehouse-in-databricks) - 4 comments, 2 upvotes
- [What are the features of Databricks?](https://www.g2.com/discussions/what-are-the-features-of-databricks) - 4 comments, 2 upvotes

### [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews)

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:** 8.8/10 (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](https://www.g2.com/sellers/google)
- **Year Founded:** 1998
- **HQ Location:** Mountain View, CA
- **Twitter:** @google  
31,899,995 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=fe4a5936665c9702418dd53c477fef5a7baea08078bb117ed67e966fc581b9ec&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1441%2F&secure%5Burl_type%5D=linkedin_company_website)  
341,888 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 appreciate the **ease of use** of Google Cloud BigQuery, enabling quick analysis of massive datasets without hassle.
- Users appreciate the **exceptional speed** of BigQuery, allowing for quick processing of large datasets seamlessly.
- Users love the **easy integration** with Google Cloud services, enabling smooth data analysis and management.
- Users appreciate the **fast querying capabilities** of Google Cloud BigQuery, allowing effortless analysis of massive datasets.
- Users appreciate the **query efficiency** of BigQuery, effortlessly processing complex queries on massive datasets with speed.

##### Cons

- Users find the **costs can escalate quickly** with Google Cloud BigQuery, requiring careful query optimization to manage expenses.
- Users struggle with **query issues** in BigQuery, facing rising costs and challenges in query optimization and troubleshooting.
- Users find **cost management challenging** with Google Cloud BigQuery due to unpredictable pricing and incidents of unexpected charges.
- Users experience **cost issues** with Google Cloud BigQuery, struggling with unexpected high bills and limited pricing visibility.
- Users find the **steep learning curve** of Google Cloud BigQuery challenging, particularly for advanced features and optimization techniques.

#### What Are Recent G2 Reviews of Google Cloud BigQuery?

**["Easy-to-Use Cloud Tool with Shareable, Saved Queries"](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12958418)**

**Rating:** 4.0/5.0 stars

_— Reetika P._

[Read full review](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12958418)

**["Scalable, Secure BigQuery That Connects Seamlessly Across Services"](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12638747)**

**Rating:** 5.0/5.0 stars

_— Aayush M._

[Read full review](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12638747)

#### What Are G2 Users Discussing About Google Cloud BigQuery?

- [Is Big Query free?](https://www.g2.com/discussions/is-big-query-free) - 3 comments, 1 upvote
- [Is BigQuery part of Google Cloud Platform?](https://www.g2.com/discussions/is-bigquery-part-of-google-cloud-platform) - 2 comments, 2 upvotes
- [What is Google BigQuery based on?](https://www.g2.com/discussions/what-is-google-bigquery-based-on) - 1 comment
- [What is Google BigQuery used for?](https://www.g2.com/discussions/what-is-google-bigquery-used-for) - 1 comment

### [Snowflake](https://www.g2.com/products/snowflake/reviews)

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:** 4.5/5.0

**Total Reviews:** 711

#### 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.](https://www.g2.com/sellers/snowflake-inc)
- **Company Website:** www.snowflake.com
- **Year Founded:** 2012
- **HQ Location:** 135 Constitution Drive, Menlo Park CA
- **Twitter:** @SnowflakeDB  
278 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ad18ff73a9b8bb34dd1b98a6ba1c6be57f7364939ad352612ecc483aba05d2b2&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsnowflake-computing%2F&secure%5Burl_type%5D=linkedin_company_website)  
11,308 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, finding it fast and effective for data sharing and analytics.
- Users value the **reliable features** of Snowflake, enjoying its intuitive interface and seamless data integration for analytics.
- Users find Snowflake's **data management capabilities** excellent for efficiently aggregating and querying across multiple datasets.
- Users admire the **seamless scalability** of Snowflake, effortlessly accommodating work demands and ensuring optimal performance.
- Users appreciate the **fast data analysis** of Snowflake, enabling quick insights without infrastructure worries.

##### Cons

- Users find Snowflake's **high costs** burdensome, especially for small businesses with limited budgets.
- Users find **feature limitations** in Snowflake, such as lack of code blocks and challenge in permissions management.
- Users find that **cost management** requires discipline, as unexpected charges can accumulate quickly without careful monitoring.
- Users find the **cost structure difficult to optimize** , leading to unexpectedly high initial expenses during implementation.
- Users find Snowflake's **limited features** in dynamic scripts and monitoring hinder flexibility and usability.

#### What Are Recent G2 Reviews of Snowflake?

**["Elastic Scaling and Fast Analytics with Snowflake"](https://www.g2.com/survey_responses/snowflake-review-13129003)**

**Rating:** 4.5/5.0 stars

_— Ravindra N._

[Read full review](https://www.g2.com/survey_responses/snowflake-review-13129003)

**["Snowflake Simplifies Data Management at Scale"](https://www.g2.com/survey_responses/snowflake-review-12898129)**

**Rating:** 4.0/5.0 stars

_— Harshil A._

[Read full review](https://www.g2.com/survey_responses/snowflake-review-12898129)

#### What Are G2 Users Discussing About Snowflake?

- [What is Snowflake used for?](https://www.g2.com/discussions/what-is-snowflake-used-for) - 2 comments, 1 upvote

### [SAP Datasphere](https://www.g2.com/products/sap-datasphere/reviews)

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:** 165

#### 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](https://www.g2.com/sellers/sap)
- **Company Website:** www.sap.com
- **Year Founded:** 1972
- **HQ Location:** Walldorf
- **Twitter:** @SAP  
297,052 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=8fd712dbd816fadfc039a60dcf8c1a3d6a48469756075586fa0be3da7e4b74d7&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsap%2F&secure%5Burl_type%5D=linkedin_company_website)  
141,955 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Business Analyst
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 40% Large, 35% 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** greatly enhances their productivity compared to other services.
- Users appreciate the **easy integrations** of SAP Datasphere, enabling seamless data access and enhanced analytics capabilities.
- Users value the **unified data management** capabilities of SAP Datasphere, enhancing data access and analytics efficiency.
- Users value the **intuitive analytics capabilities** of SAP Datasphere, simplifying data integration and enhancing insights generation.
- Users value the **seamless collaboration** SAP Datasphere offers, enhancing integration and data accessibility across SAP products.

##### Cons

- Users are frustrated with the **slow performance** of SAP Datasphere, especially when handling large datasets and complex tasks.
- Users note the **expensive pricing** of SAP Datasphere, which can be a significant drawback for new users.
- Users often face **performance issues** with SAP Datasphere, particularly with speed and large dataset handling.
- Users face **integration issues** with SAP Datasphere, requiring middleware solutions and causing performance challenges, especially for beginners.
- Users find the **complex setup** of SAP Datasphere frustrating due to vague error messages and steep learning curve.

#### What Are Recent G2 Reviews of SAP Datasphere?

**["SAP Datasphere A Powerful Platform for Data Integration and Real-Time Business Insights"](https://www.g2.com/survey_responses/sap-datasphere-review-12817894)**

**Rating:** 5.0/5.0 stars

_— Muzammil M._

[Read full review](https://www.g2.com/survey_responses/sap-datasphere-review-12817894)

**["SAP Datasphere Simplifies Multi-Source Data Consolidation and Integration"](https://www.g2.com/survey_responses/sap-datasphere-review-12739150)**

**Rating:** 4.5/5.0 stars

_— Nijat I._

[Read full review](https://www.g2.com/survey_responses/sap-datasphere-review-12739150)

#### What Are G2 Users Discussing About SAP Datasphere?

- [What is SAP Data Warehouse Cloud used for?](https://www.g2.com/discussions/what-is-sap-data-warehouse-cloud-used-for) - 1 comment

### [Amazon Redshift](https://www.g2.com/products/amazon-redshift/reviews)

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)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd)
- **Year Founded:** 2006
- **HQ Location:** Seattle, WA
- **Twitter:** @awscloud  
2,232,483 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=072881eee28a2afe24f8d1bda9f20e3e146b9fb4b214f216411ce2ed6898b31e&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Famazon-web-services%2F&secure%5Burl_type%5D=linkedin_company_website)  
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 value the **fast querying capabilities** of Amazon Redshift, enabling efficient analysis of large datasets seamlessly.
- Users praise the **easy integrations** with other software, enhancing data solutions within the Amazon Redshift ecosystem.
- Users find Amazon Redshift's **ease of use** exceptional, facilitating quick access and efficient data management.
- Users value the **easy integrations** of Amazon Redshift, enhancing their ability to build seamless data solutions.
- Users praise the **impressive speed and scalability** of Amazon Redshift, optimizing data management and query performance.

##### Cons

- Users find **feature limitations** in Redshift, especially regarding advanced analytics and multi-language support for coding.
- Users note significant **software limitations** with Redshift, particularly regarding cost and performance issues with complex queries.
- Users find the **complexity of optimizations** in Amazon Redshift burdensome, requiring significant management and maintenance effort.
- Users face **query issues** with Amazon Redshift, requiring extensive optimization and management to maintain performance.
- Users find the **query optimization process cumbersome** , as it requires significant effort and specialized knowledge for efficiency.

#### What Are Recent G2 Reviews of Amazon Redshift?

**["Scalable and Efficient Cloud Data Platform"](https://www.g2.com/survey_responses/amazon-redshift-review-12872150)**

**Rating:** 4.5/5.0 stars

_— Swaroop W._

[Read full review](https://www.g2.com/survey_responses/amazon-redshift-review-12872150)

**["Powerful Analytics Tool with Some Flexibility Limitations"](https://www.g2.com/survey_responses/amazon-redshift-review-12781722)**

**Rating:** 4.0/5.0 stars

_— Atharva P._

[Read full review](https://www.g2.com/survey_responses/amazon-redshift-review-12781722)

#### What Are G2 Users Discussing About Amazon Redshift?

- [What is Amazon Redshift used for?](https://www.g2.com/discussions/what-is-amazon-redshift-used-for)
- [Is AWS redshift a database?](https://www.g2.com/discussions/is-aws-redshift-a-database) - 1 comment
- [When can I use Amazon redshift?](https://www.g2.com/discussions/when-can-i-use-amazon-redshift) - 3 comments
- [What are the characteristics of redshift?](https://www.g2.com/discussions/what-are-the-characteristics-of-redshift) - 2 comments
- [What does Amazon redshift do?](https://www.g2.com/discussions/what-does-amazon-redshift-do) - 2 comments

### [Teradata Autonomous Knowledge Platform](https://www.g2.com/products/teradata-autonomous-knowledge-platform/reviews)

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:** 356

#### 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?

- **Seller:** [Teradata Autonomous Knowledge Platform](https://www.g2.com/sellers/teradata-autonomous-knowledge-platform)
- **Year Founded:** 1979
- **HQ Location:** San Diego, CA
- **Twitter:** @Teradata  
93,113 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=06895b9a8db4fa478ba7da480ccd214a14ef698abd028e4642e62f189e82b650&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1466%2F&secure%5Burl_type%5D=linkedin_company_website)  
9,901 employees on LinkedIn®
- **Ownership:** NYSE:TDC

#### 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 the Teradata Autonomous Knowledge Platform, especially for processing large data volumes efficiently.
- Users value the **high performance query execution** in Teradata, enhancing their business analytics capabilities significantly.
- Users value the **scalability** of Teradata Autonomous Knowledge Platform, enhancing data integration and operational efficiency significantly.
- Users commend the **high performance and speed** of Teradata, efficiently processing large datasets without issues.
- Users value the **fast processing of large datasets** with Teradata, praising its performance and stability during operations.

##### Cons

- Users find the **steep learning curve** of Teradata Autonomous Knowledge Platform challenging, impacting adoption and productivity temporarily.
- Users find the **steep learning curve** of Teradata Autonomous Knowledge Platform challenging, particularly for those lacking technical expertise.
- Users find the **complexity** of Teradata's platform challenging, particularly for non-technical users and new adopters.
- Users express concerns over the **cost management requirements** needed to avoid potential misusage and performance issues.
- Users feel the **high cost** of Teradata Autonomous Knowledge Platform is a significant drawback affecting accessibility.

#### What Are Recent G2 Reviews of Teradata Autonomous Knowledge Platform?

**["Teradata Vantage Fast Query Performance and Strong Analytics for Big Data"](https://www.g2.com/survey_responses/teradata-autonomous-knowledge-platform-review-12821668)**

**Rating:** 5.0/5.0 stars

_— Muzammil M._

[Read full review](https://www.g2.com/survey_responses/teradata-autonomous-knowledge-platform-review-12821668)

**["Teradata Vantage Excels at Big Data Processing and Advanced Analytics"](https://www.g2.com/survey_responses/teradata-autonomous-knowledge-platform-review-12739181)**

**Rating:** 4.5/5.0 stars

_— Nijat I._

[Read full review](https://www.g2.com/survey_responses/teradata-autonomous-knowledge-platform-review-12739181)

#### What Are G2 Users Discussing About Teradata Autonomous Knowledge Platform?

- [What does Teradata Data Lab do?](https://www.g2.com/discussions/what-does-teradata-data-lab-do)
- [Is Teradata a premiership?](https://www.g2.com/discussions/is-teradata-a-premiership)
- [What is Teradata Vantage?](https://www.g2.com/discussions/what-is-teradata-vantage)
- [How much does Teradata cost?](https://www.g2.com/discussions/how-much-does-teradata-cost)
- [What is Sandbox in Teradata?](https://www.g2.com/discussions/what-is-sandbox-in-teradata)

### [VMware Greenplum](https://www.g2.com/products/vmware-greenplum/reviews)

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: 8.7/10)
- **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](https://www.g2.com/sellers/broadcom-ab3091cd-4724-46a8-ac89-219d6bc8e166)
- **Year Founded:** 1991
- **HQ Location:** San Jose, CA
- **Twitter:** @broadcom  
63,909 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=093adce8015fea9ef126312884b465dc8e3c20e17dcb12fbb77a7bd82577e7a5&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fbroadcom%2F&secure%5Burl_type%5D=linkedin_company_website)  
55,094 employees on LinkedIn®
- **Ownership:** NASDAQ: CA

#### 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?

**["Open-Source MPP Database That Supercharges Large-Scale Analytics"](https://www.g2.com/survey_responses/vmware-greenplum-review-12872814)**

**Rating:** 5.0/5.0 stars

_— deepeshkumar G._

[Read full review](https://www.g2.com/survey_responses/vmware-greenplum-review-12872814)

**["Greenplum - BIg Data Database"](https://www.g2.com/survey_responses/vmware-greenplum-review-6752415)**

**Rating:** 4.0/5.0 stars

_— Naveen A._

[Read full review](https://www.g2.com/survey_responses/vmware-greenplum-review-6752415)

#### What Are G2 Users Discussing About VMware Greenplum?

- [Who uses Greenplum?](https://www.g2.com/discussions/who-uses-greenplum)
- [What type of database is greenplum?](https://www.g2.com/discussions/what-type-of-database-is-greenplum)
- [What is Greenplum software?](https://www.g2.com/discussions/what-is-greenplum-software)
- [What is greenplum used for?](https://www.g2.com/discussions/what-is-greenplum-used-for)

### [IBM watsonx.data](https://www.g2.com/products/ibm-watsonx-data/reviews)

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:** 166

#### How Do G2 Users Rate IBM watsonx.data?

- **Ease of Use:** 8.2/10 (Category avg: 8.7/10)
- **Data Governance:** 9.4/10 (Category avg: 8.4/10)
- **Data Security:** 9.6/10 (Category avg: 8.8/10)
- **Scalability:** 9.1/10 (Category avg: 8.5/10)

#### Who Is the Company Behind IBM watsonx.data?

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Company Website:** www.ibm.com
- **Year Founded:** 1911
- **HQ Location:** Armonk, New York, United States
- **Twitter:** @IBMSecurity  
74,660 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=14b544adaece4fdbc987f1d7f7028048c22259946811200cc751263825586af9&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1009%2F&secure%5Burl_type%5D=linkedin_company_website)  
328,202 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Software Engineer, CEO
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 33% 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 tasks.
- Users value the **organized data integration** and intuitive interface of IBM watsonx.data, enhancing efficiency and analytics.
- Users value the **organized and efficient data management** of IBM watsonx.data, enhancing analytics and reporting tasks seamlessly.
- Users value the **seamless data source integration** in IBM watsonx.data, enhancing flexibility and efficiency for diverse projects.
- Users value the **ability to unify data across hybrid environments** , enhancing flexibility and driving informed decision-making.

##### Cons

- Users find the **learning curve steep** , making initial setup and navigation challenging for newcomers to IBM watsonx.data.
- Users find the **complexity** of setting up IBM watsonx.data a barrier, especially for newcomers to IBM technologies.
- Users find the **pricing steep** for IBM watsonx.data, making it less accessible for smaller businesses and projects.
- Users find the **difficult setup** of IBM watsonx.data time-consuming, with a steep learning curve and complex configurations.
- Users find IBM watsonx.data **difficult to navigate** , especially for beginners and those unfamiliar with AI and data analytics.

#### What Are Recent G2 Reviews of IBM watsonx.data?

**["Powerful Query Performance and Governance, But a Steep Onboarding Learning Curve"](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12836202)**

**Rating:** 4.0/5.0 stars

_— Arkajit D._

[Read full review](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12836202)

**["Unified Data Management with Learning Curve"](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12817742)**

**Rating:** 5.0/5.0 stars

_— Anchal P._

[Read full review](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12817742)

### [IBM Netezza Performance Server](https://www.g2.com/products/ibm-netezza-performance-server/reviews)

Integrates database, server, storage and analytics into a single system with petabyte scalability. Fast analytics Provides a high-performance, massively parallel system that enables you to gain insight from your data and perform analytics on very large data volumes. Smart, efficient queries Simplifies analytics by consolidating all activity in one place, where the data resides. Simplified infrastructure Easy to deploy and manage; simplifies your data warehouse and analytic infrastructure. Does not require tuning, indexing or aggregated tables and needs minimal administration. Advanced security Enhanced data security is provided through self-encrypting drives as well as support for the Kerberos authentication protocol. Integrated platform Supports thousands of users, unifying data warehouse, Hadoop and business intelligence with advanced analytics.

**Average Rating:** 4.1/5.0

**Total Reviews:** 68

#### How Do G2 Users Rate IBM Netezza Performance Server?

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

#### Who Is the Company Behind IBM Netezza Performance Server?

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Year Founded:** 1911
- **HQ Location:** Armonk, New York, United States
- **Twitter:** @IBMSecurity  
74,660 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=14b544adaece4fdbc987f1d7f7028048c22259946811200cc751263825586af9&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1009%2F&secure%5Burl_type%5D=linkedin_company_website)  
328,202 employees on LinkedIn®
- **Ownership:** SWX:IBM

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services, Banking
- **Company Size:** 62% Large, 27% Medium

#### What Do G2 Reviewers Say About IBM Netezza Performance Server?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **exceptional speed** of IBM Netezza Performance Server, enhancing data analysis and handling complex queries efficiently.
- Users rave about the **exceptional speed and efficiency** of IBM Netezza Performance Server, enhancing data analysis and processing tasks.
- Users value the **user-friendly interface** of IBM Netezza Performance Server, making data analysis and integration effortless.
- Users praise the **exceptional processing speed** of IBM Netezza Performance Server, enhancing data analysis and query efficiency.
- Users commend the **high processing speed and efficiency** of IBM Netezza Performance Server for seamless data management.

##### Cons

- Users identify the **high cost** of IBM Netezza Performance Server as a significant challenge, particularly for smaller enterprises.
- Users find the **high maintenance costs** of IBM Netezza Performance Server a barrier, particularly for smaller businesses.
- Users find **integration issues** challenging when connecting IBM Netezza Performance Server with other software tools.
- Users find the **limited customization** options frustrating, which can hinder software integration and flexibility.
- Users experience **slow performance** with IBM Netezza Performance Server when handling millions of records, affecting query times.

#### What Are Recent G2 Reviews of IBM Netezza Performance Server?

**["Unleashing intelligence with IBM Netezza, driving data analysis and expediting Insights."](https://www.g2.com/survey_responses/ibm-netezza-performance-server-review-9011395)**

**Rating:** 5.0/5.0 stars

_— Gunavardhan R._

[Read full review](https://www.g2.com/survey_responses/ibm-netezza-performance-server-review-9011395)

**["Efficiency Unleashed: A Comprehensive Review of IBM Netezza Performance Server"](https://www.g2.com/survey_responses/ibm-netezza-performance-server-review-8891188)**

**Rating:** 4.0/5.0 stars

_— Verified User in Food Production_

[Read full review](https://www.g2.com/survey_responses/ibm-netezza-performance-server-review-8891188)

#### What Are G2 Users Discussing About IBM Netezza Performance Server?

- [What is IBM Netezza Performance Server used for?](https://www.g2.com/discussions/what-is-ibm-netezza-performance-server-used-for)
- [What is IBM PureData?](https://www.g2.com/discussions/what-is-ibm-puredata)
- [What is netezza used for?](https://www.g2.com/discussions/what-is-netezza-used-for)
- [Is Netezza end of life?](https://www.g2.com/discussions/is-netezza-end-of-life)
- [What is IBM PDA?](https://www.g2.com/discussions/what-is-ibm-pda)

### [IBM Db2](https://www.g2.com/products/ibm-db2/reviews)

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:** 598

#### 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](https://www.g2.com/sellers/ibm)
- **Year Founded:** 1911
- **HQ Location:** Armonk, New York, United States
- **Twitter:** @IBMSecurity  
74,660 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=14b544adaece4fdbc987f1d7f7028048c22259946811200cc751263825586af9&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1009%2F&secure%5Burl_type%5D=linkedin_company_website)  
328,202 employees on LinkedIn®
- **Ownership:** SWX:IBM

#### Who Uses This Product?

- **Who Uses This:** Software Engineer, Senior 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 **exceptional performance** of IBM Db2, praising its reliability and scalability for critical workloads.
- Users value the **high reliability** of IBM Db2, ensuring excellent performance and stability for critical workloads.
- Users appreciate the **scalability** of IBM Db2, finding it ideal for high-performance, enterprise-level applications.
- Users highlight the **strong security** of IBM Db2, making it a reliable choice for critical workloads across industries.
- Users appreciate the **ease of use** of IBM Db2, highlighting its seamless integration and user-friendly features.

##### Cons

- Users find the **complex setup** of IBM Db2 challenging, often leading to a steep learning curve for effective use.
- Users find IBM Db2 to be **expensive** , with high licensing costs and significant resource demands impacting their budget.
- Users face a **steep learning curve** with IBM Db2, making setup and administration challenging for newcomers.
- Users find IBM Db2's setup **complex** , with a steep learning curve and challenges in documentation and support.
- Users find the **difficult setup** of IBM Db2 challenging, citing complexity and steep learning curves as significant barriers.

#### What Are Recent G2 Reviews of IBM Db2?

**["Rock-Solid Performance, Great Features"](https://www.g2.com/survey_responses/ibm-db2-review-12540353)**

**Rating:** 5.0/5.0 stars

_— Ramesh Babu C._

[Read full review](https://www.g2.com/survey_responses/ibm-db2-review-12540353)

**["Comprehensive Review of DB2 on IBM i (AS/400)"](https://www.g2.com/survey_responses/ibm-db2-review-9863177)**

**Rating:** 4.5/5.0 stars

_— Swapnil T._

[Read full review](https://www.g2.com/survey_responses/ibm-db2-review-9863177)

#### What Are G2 Users Discussing About IBM Db2?

- [What is IBM Db2 used for?](https://www.g2.com/discussions/what-is-ibm-db2-used-for) - 1 comment
- [What does Ibm Dashdb do?](https://www.g2.com/discussions/what-does-ibm-dashdb-do) - 1 comment
- [What database does IBM use?](https://www.g2.com/discussions/what-database-does-ibm-use)
- [What is DB2 Warehouse?](https://www.g2.com/discussions/what-is-db2-warehouse)
- [What is IBM dashDB?](https://www.g2.com/discussions/what-is-ibm-dashdb)

### [SQL Server 2019](https://www.g2.com/products/sql-server-2019/reviews)

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: 8.7/10)
- **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](https://www.g2.com/sellers/microsoft)
- **Year Founded:** 1975
- **HQ Location:** Redmond, Washington
- **Twitter:** @microsoft  
13,091,739 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=9458f51bd6ded48ad432a804f19ad736469f007787569b63827154231c315630&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fmicrosoft%2F&secure%5Burl_type%5D=linkedin_company_website)  
231,632 employees on LinkedIn®
- **Ownership:** MSFT

#### 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 **smooth integration with .NET Core** in SQL Server 2019, enhancing backend development and performance.
- Users value the **advanced indexing and optimized data retrieval** in SQL Server 2019 for handling complex queries effectively.

##### Cons

- Users find the **high licensing costs** of SQL Server 2019 to be a barrier, especially for smaller projects.

#### What Are Recent G2 Reviews of SQL Server 2019?

**["SQL Server 2019 Review"](https://www.g2.com/survey_responses/sql-server-2019-review-10693637)**

**Rating:** 4.5/5.0 stars

_— Kavya S._

[Read full review](https://www.g2.com/survey_responses/sql-server-2019-review-10693637)

**["Improved performance and scalability: an excellent experience"](https://www.g2.com/survey_responses/sql-server-2019-review-12241600)**

**Rating:** 5.0/5.0 stars

_— Verified User in Computer & Network Security_

[Read full review](https://www.g2.com/survey_responses/sql-server-2019-review-12241600)

#### What Are G2 Users Discussing About SQL Server 2019?

- [What is SQL Server 2019 used for?](https://www.g2.com/discussions/what-is-sql-server-2019-used-for) - 1 comment
- [What is SQL Server and its features?](https://www.g2.com/discussions/sql-server-2019-what-is-sql-server-and-its-features)
- [Why is SQL Server 2019?](https://www.g2.com/discussions/why-is-sql-server-2019)
- [Is SQL Server 2019 released?](https://www.g2.com/discussions/is-sql-server-2019-released)
- [What are the new features in SQL Server 2019?](https://www.g2.com/discussions/what-are-the-new-features-in-sql-server-2019)

### [ILUM](https://www.g2.com/products/ilum-ilum/reviews)

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

**Average Rating:** 4.9/5.0

**Total Reviews:** 23

#### 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](https://www.g2.com/sellers/ilum)
- **Company Website:** ilum.cloud
- **Year Founded:** 2019
- **HQ Location:** Santa Fe, US
- **Twitter:** @IlumCloud  
19 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=1fbd1d37d0b9f349ede11be8e26481a08073e5b7f53b306080db734d9789f8fb&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Filum-cloud%2F&secure%5Burl_type%5D=linkedin_company_website)  
4 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 appreciate the **ease of use** of ILUM, enjoying seamless integration and a smooth workflow for managing data.
- Users value the **seamless integration** of ILUM with existing systems, enhancing efficiency in data management and analytics.
- Users appreciate the **seamless integrations** of ILUM, enhancing data management and analytics with a unified, efficient platform.
- Users value the **quick and seamless setup** of ILUM, appreciating its ease of integration and efficiency.
- Users appreciate the **easy integrations** of ILUM, smoothly fitting into existing systems without major rewrites.

##### Cons

- Users find the **complex setup** for advanced configurations of ILUM can be challenging for newcomers to navigate.
- Users find the **difficult setup** process of ILUM challenging, requiring significant effort and experimentation to optimize configurations.
- Users find the **learning curve steep** for advanced features in ILUM, requiring time to adapt and configure settings.
- Users note that **UI improvements** are needed for easier access to advanced settings and configurations in ILUM.
- Users find some aspects of ILUM's setup **complex and unintuitive** , requiring considerable effort to configure effectively.

#### What Are Recent G2 Reviews of ILUM?

**["From Hadoop to K8s with lower TCO"](https://www.g2.com/survey_responses/ilum-review-11862422)**

**Rating:** 5.0/5.0 stars

_— Mark D._

[Read full review](https://www.g2.com/survey_responses/ilum-review-11862422)

**["Seamless Integration and Unified Features for Advanced Users"](https://www.g2.com/survey_responses/ilum-review-11904273)**

**Rating:** 5.0/5.0 stars

_— Jan L._

[Read full review](https://www.g2.com/survey_responses/ilum-review-11904273)

### [Rubrik](https://www.g2.com/products/rubrik/reviews)

Rubrik is the leading cyber resilience and data protection company with a mission to secure the world’s data. Rubrik pioneered Zero Trust Data SecurityTM to help organizations achieve business resilience against cyberattacks, malicious insiders, and operational disruptions. Rubrik Security Cloud, built with a Zero Trust design and powered by machine learning, delivers complete cyber resilience in a single platform across enterprise, cloud, and SaaS. Rubrik’s platform automates data policy management and enforcement, safeguards sensitive data, delivers data threat analytics and response, and orchestrates rapid cyber and operational recovery.

**Average Rating:** 4.6/5.0

**Total Reviews:** 276

#### How Do G2 Users Rate Rubrik?

- **Ease of Use:** 9.1/10 (Category avg: 8.7/10)
- **Data Governance:** 9.0/10 (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 Rubrik?

- **Seller:** [Rubrik](https://www.g2.com/sellers/rubrik)
- **Company Website:** www.rubrik.com
- **Year Founded:** 2014
- **HQ Location:** Palo Alto, California
- **Twitter:** @rubrikInc  
44,021 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=62c2fafa7bcff10fab6b5074fb81b0b19d99e38b217b5c2e1605adbbdb7da7ff&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F4840301%2F&secure%5Burl_type%5D=linkedin_company_website)  
5,110 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** System Administrator
- **Top Industries:** Information Technology and Services, Hospital & Health Care
- **Company Size:** 48% Large, 33% Medium

#### What Do G2 Reviewers Say About Rubrik?

_AI-generated summary from verified user reviews_

##### Pros

- Users find Rubrik's **ease of use** and intuitive setup significantly streamline backup and recovery management.
- Users value how Rubrik’s backup solutions provide **ease of implementation** and efficient management without impacting applications.
- Users appreciate the **reliability** of Rubrik, ensuring dependable backups and robust data protection with ease of use.
- Users appreciate the **backup efficiency** of Rubrik, enabling seamless server and database protection with minimal impact.
- Users love Rubrik's **user-friendly interface** , making navigation and recovery processes efficient and straightforward.

##### Cons

- Users find Rubrik to be **expensive** , yet acknowledge that its value often justifies the high cost.
- Users find the **limited features** of Rubrik restricting their backup and reporting capabilities, impacting overall functionality.
- Users find the **complexity of advanced features** and integrations with Microsoft 365 data somewhat overwhelming and cumbersome.
- Users find **missing features** like limited database support and inadequate search options in Rubrik, hindering functionality.
- Users express concern over the **cost management** of Rubrik, particularly during yearly renewal processes.

#### What Are Recent G2 Reviews of Rubrik?

**["Evaluating Rubrik for Enterprise Data Protection"](https://www.g2.com/survey_responses/rubrik-review-13103366)**

**Rating:** 4.5/5.0 stars

_— Rayanne A._

[Read full review](https://www.g2.com/survey_responses/rubrik-review-13103366)

**["Reliable, hands-free backup that actually gives you peace of mind"](https://www.g2.com/survey_responses/rubrik-review-13070838)**

**Rating:** 5.0/5.0 stars

_— Shalu G._

[Read full review](https://www.g2.com/survey_responses/rubrik-review-13070838)

#### What Are G2 Users Discussing About Rubrik?

- [What operating system does rubrik use?](https://www.g2.com/discussions/what-operating-system-does-rubrik-use)
- [How is rubrik different?](https://www.g2.com/discussions/how-is-rubrik-different)
- [What makes rubrik unique?](https://www.g2.com/discussions/what-makes-rubrik-unique)
- [What is rubrik used for?](https://www.g2.com/discussions/what-is-rubrik-used-for)

### [Dremio](https://www.g2.com/products/dremio/reviews)

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](https://www.g2.com/sellers/dremio)
- **Year Founded:** 2015
- **HQ Location:** Santa Clara, California
- **Twitter:** @dremio  
5,112 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=69ad9580be02795c06f73dc00556a9c4aa0acb9aa5cce310d34ccd1e0c10cc44&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdremio%2F&secure%5Burl_type%5D=linkedin_company_website)  
370 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's **ease of use** exceptional, enabling quick data sharing and seamless integration with multiple tools.
- Users appreciate the **seamless integrations** of Dremio with tools like Power BI and Tableau for efficient data management.
- Users value the **exceptional performance** of Dremio for accelerating query speed and facilitating efficient data workflows.
- Users value the **SQL support** in Dremio, enhancing data connectivity and integration with various analytics platforms.
- Users appreciate the **advanced data management capabilities** of Dremio, enhancing data collection and analysis across various platforms.

##### Cons

- Users find the **initial setup complicated** and experience a steep learning curve that hampers their productivity.
- Users report that **customer support can be slow** , leading to delays in resolving issues and frustration.
- Users note a **steep learning curve** with Dremio, making setup and feature understanding challenging for beginners.
- Users find the **difficult setup** of Dremio challenging and time-consuming, often requiring external resources for assistance.
- Users feel that the **documentation is poor** , often forcing them to seek help outside the provided resources.

#### What Are Recent G2 Reviews of Dremio?

**["Evaluating Dremio for Enterprise Data Analytics"](https://www.g2.com/survey_responses/dremio-review-13102983)**

**Rating:** 4.5/5.0 stars

_— Guilherme A._

[Read full review](https://www.g2.com/survey_responses/dremio-review-13102983)

**["Flexible SQL for Handling Data from Many Sources"](https://www.g2.com/survey_responses/dremio-review-12709566)**

**Rating:** 4.5/5.0 stars

_— Tariel (Tato) B._

[Read full review](https://www.g2.com/survey_responses/dremio-review-12709566)

#### What Are G2 Users Discussing About Dremio?

- [What is Dremio used for?](https://www.g2.com/discussions/what-is-dremio-used-for)
- [What is drill in Hadoop?](https://www.g2.com/discussions/what-is-drill-in-hadoop)
- [What is a Dremio reflection?](https://www.g2.com/discussions/what-is-a-dremio-reflection) - 1 comment
- [Is Dremio free?](https://www.g2.com/discussions/is-dremio-free)
- [What is Dremio software?](https://www.g2.com/discussions/what-is-dremio-software)

### [Starburst](https://www.g2.com/fr/products/starburst/reviews)

Starburst est la plateforme de données pour l'analytique, les applications et l'IA, unifiant les données à travers les clouds et sur site pour accélérer l'innovation en IA. Des organisations, allant des startups aux entreprises du Fortune 500 dans plus de 60 pays, comptent sur Starburst pour un accès rapide aux données, une collaboration sans faille et une gouvernance de niveau entreprise sur un data lakehouse hybride ouvert. Où que se trouvent les données, Starburst libère leur plein potentiel, alimentant les données et l'IA du développement au déploiement. En pérennisant l'architecture des données, Starburst aide les entreprises à stimuler l'innovation avec l'IA. Apprenez-en plus sur starburst.ai

**Average Rating:** 4.4/5.0

**Total Reviews:** 99

#### How Do G2 Users Rate Starburst?

- **Facilité d’utilisation:** 9.0/10 (Category avg: 8.7/10)
- **Gouvernance des données:** 7.6/10 (Category avg: 8.4/10)
- **Sécurité des données:** 8.4/10 (Category avg: 8.8/10)
- **Évolutivité:** 8.9/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Starburst?

- **Vendeur:** [Starburst](https://www.g2.com/fr/sellers/starburst)
- **Site Web de l'entreprise:** www.starburst.io
- **Année de fondation:** 2017
- **Emplacement du siège social:** Boston, MA
- **Twitter:** @starburstdata  
3,454 abonnés Twitter
- **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=6e8e7115417f25433cd515a6e146b579fb0353f1130e9be509f37e24c1adb7f6&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fstarburstdata%2F&secure%5Burl_type%5D=linkedin_company_website)  
539 employés sur LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Technologie de l'information et services, Services financiers
- **Company Size:** 46% Large, 32% Small

#### What Do G2 Reviewers Say About Starburst?

_AI-generated summary from verified user reviews_

##### Pros

- Les utilisateurs soulignent les capacités de **requêtes rapides** de Starburst, permettant un accès et une analyse rapides des données à partir de diverses sources.
- Les utilisateurs apprécient l' **efficacité des requêtes** de Starburst, permettant un accès rapide à diverses sources de données sans effort.
- Les utilisateurs apprécient l' **intégration transparente** avec diverses sources de données, ce qui améliore considérablement l'accès aux données et l'efficacité de l'analyse.
- Les utilisateurs apprécient la **facilité d'utilisation** de Starburst, permettant un accès efficace aux données et une analyse en temps réel à partir de diverses sources.
- Les utilisateurs louent Starburst pour ses **performances supérieures** , récupérant rapidement des données précises et améliorant la productivité globale.

##### Cons

- Les utilisateurs rencontrent souvent des **problèmes de requête** avec Starburst, le trouvant moins efficace pour les requêtes complexes par rapport aux éditeurs SQL traditionnels.
- Les utilisateurs trouvent la **complexité de l'installation initiale** de Starburst difficile, surtout en ce qui concerne la configuration et l'optimisation des requêtes.
- Les utilisateurs remarquent une **courbe d'apprentissage abrupte** lors de la configuration de Starburst, rendant l'intégration et l'optimisation difficiles pour les nouveaux utilisateurs.
- Les utilisateurs rencontrent souvent une **performance lente** sur Starburst, surtout pendant les périodes de forte utilisation et avec des requêtes complexes.
- Les utilisateurs signalent des **problèmes de performance** avec Starburst, surtout lors de l'exécution de requêtes complexes, entraînant des ralentissements significatifs.

#### What Are Recent G2 Reviews of Starburst?

**["Transformation de l'analyse d'entreprise et activation de l'IA grâce à la fédération de données"](https://www.g2.com/fr/survey_responses/starburst-review-11962416)**

**Rating:** 4.0/5.0 stars

_— Utilisateur vérifié à Services financiers_

[Read full review](https://www.g2.com/fr/survey_responses/starburst-review-11962416)

**["Revue de Starburst Enterprise"](https://www.g2.com/fr/survey_responses/starburst-review-10604384)**

**Rating:** 4.0/5.0 stars

_— Rajiv B._

[Read full review](https://www.g2.com/fr/survey_responses/starburst-review-10604384)

#### What Are G2 Users Discussing About Starburst?

- [What does Starburst do?](https://www.g2.com/fr/discussions/what-does-starburst-do)
- [What is Starburst Presto?](https://www.g2.com/fr/discussions/what-is-starburst-presto)
- [What is Starburst tech?](https://www.g2.com/fr/discussions/what-is-starburst-tech)
- [What does Starburst data do?](https://www.g2.com/fr/discussions/what-does-starburst-data-do)

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[Browse Data Warehouse Themes](/categories/data-warehouse/themes)

 ![Shalaka Joshi](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Shalaka Joshi")
SJ

Researched and written by [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)

Updated 

Products classified in the overall Data Warehouse category are similar in many regards and help companies of all sizes solve their business problems. However, enterprise business features, pricing, setup, and installation differ from businesses of other sizes, which is why we match buyers to the right Enterprise Business Data Warehouse to fit their needs. Compare product ratings based on reviews from enterprise users or connect with one of G2's buying advisors to find the right solutions within the Enterprise Business Data Warehouse category.

In addition to qualifying for inclusion in the Data Warehouse Solutions category, to qualify for inclusion in the Enterprise Business Data Warehouse Solutions category, a product must have at least 10 reviews left by a reviewer from an enterprise business.

Top Tools at a Glance

| 

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Serverless SQL analytics on petabyte-scale datasets

 | 

User Review

"Easy-to-Use Cloud Tool with Shareable, Saved Queries"

 |
| 

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Unified lakehouse warehousing with governed analytics

 | 

User Review

"Helpful for Managing and Analyzing Operational Data"

 |
| 

 | 

Elastic multi-workload cloud data warehousing

 | 

User Review

"Elastic Scaling and Fast Analytics with Snowflake"

 |
| 

 | 

SAP-native semantic data warehousing with virtualization

 | 

User Review

"SAP Datasphere Simplifies Multi-Source Data Consolidation and Integration"

 |
| 

 | 

Federated lakehouse querying without data movement

 | 

User Review

"Powerful Query Performance and Governance, But a Steep Onboarding Learning Curve"

 |
| 

 | 

AWS-native analytical data warehousing at petabyte scale

 | 

User Review

"Scalable and Efficient Cloud Data Platform"

 |
| 

 | 

Massively parallel enterprise data warehousing with in-database analytics

 | 

User Review

"Teradata Vantage Fast Query Performance and Strong Analytics for Big Data"

 |
| 

 | 

Relational data warehousing with Microsoft-native analytics

 | 

User Review

"SQL Server 2019 Review"

 |
| 

 | 

Petabyte-scale OLAP with MPP parallelism

 | 

User Review

"Open-Source MPP Database That Supercharges Large-Scale Analytics"

 |
| 

 | 

Hybrid OLTP and OLAP warehouse workloads

 | 

User Review

"Rock-Solid Performance, Great Features"

 |

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Show More

* * *

## How Do You Choose the Right Data Warehouse Solutions?

### What You Should Know About Data Warehouse Solutions

### What are Data Warehouse Solutions?

Data warehouse technology is used as a storage mechanism that pulls data from multiple disparate data sources into one single data store in an organized and efficient way to enable analytics and reporting for better decision-making. It is different from traditional database technology which is only capable of recording data. Data warehouse solutions are designed with integration and analysis in mind; and not like other databases that are designed to be queried in a variety of ways. This helps users without knowledge of SQL or other common querying languages to extract information from storage.

A data warehouse acts as a single data repository that is an analytical and reporting database used to store historical data pulled from various disparate data sources. It also enables data retrieval through complex queries using online analytical processing (OLAP).

Most data warehouse technology comes with features for data cleansing and normalization, so data can be stored in a variety of forms. This allows data from sales, marketing, research, and other departments to be stored in their natural forms but cleansed for comparative analysis.

#### What Types of Data Warehouse Solutions Exist?

Data warehouse solutions enable users to gain critical insights into their data through improved seamless self-service business intelligence (BI) capabilities. Though the purpose of the software remains the same, it differs in the mode of deployment and architecture. A data warehouse solution can be deployed both on the cloud and on-premises. 

**Cloud data warehouse **

With cloud data warehouses, businesses can scale horizontally to hold increased storage and compute requirements. A data warehouse deployed on the cloud provides an improved infrastructure that lets companies focus more on delivering better and faster insights rather than managing a full house of servers on premises. These solutions provide cost control as organizations pay for what they use.

**On-premises or license data warehouse **

An on-premises data warehouse software lets organizations buy one time, deploy in-house, and enable control over their hardware and software infrastructure. This deployment solution requires a consultant to help with installation and ongoing support. One advantage of on-premises data warehouse solutions is that it gives complete control and access over the data within an organization, helping minimize security risks.

### What are the Common Features of Data Warehouse Solutions?

Data warehouses help organizations execute an effective data strategy, they feed structured and standardized data into BI tools which provide data professionals with high-level insights for decision-making. The following are some core features of data warehouse software: 

**Data source connections:** Data warehouses typically rely on a range of data sources. The data can come from disparate sources, such as spreadsheets, banking systems, and software that ranges from SQL servers and relational databases to legacy systems. This feature helps users pull data that they hope to use during the decision-making process.

**Data mart:** Data warehouses are organized into individual subsections. These segmented storage locations within the data warehouse are typically relevant to an individual team or department. Data warehouse solutions enable users to create data marts within them.

**Scaling:** Scaling allows the data warehouse to expand storage capacity and functionality while maintaining balanced workloads. This helps facilitate the growing demand for requests and expanding sets of information.

**Autoscaling**** :** While many tools allow administrators to control scaling storage, autoscaling features help to reduce the manual aspects. This is done with automation tools or bots that scale services and data automatically or on demand.

**Data sharing:** Data sharing features offer collaborative functionality for sharing queries and data sets. These can be edited or maintained between users and potentially sent to customers or business partners.

**Data discovery**** :** Search tools provide the ability to search vast, global data sets to find relevant information. This allows users self-service access and navigation to multiple datasets.

**Data modeling**** :** Data modeling tools help users structure and edit data in a manner that enables quick and accurate insight extraction. They also help translate raw data into a more digestible format.

**Compliance**** :** Compliance features monitor assets and enforce security policies. This also helps to audit assets to support compliance with personally identifiable information (PII), General Data Protection Regulation (GDPR), Health Insurance Portability and Accountability Act (HIPAA), and other regulatory standards.

**Data staging:** Data staging areas are used to normalize and structure information. These transitional storage areas are often used during extract, transform, and load (ETL) processes where information is transformed, consolidated, aligned, and eventually exported.

**Presentation tools:** Once data has been cleansed and normalized within the staging area, it will be transferred to data marts for access from users. They may be exported at that point or paired with BI tools for further visualization and data analysis.

**Integration tools:** Integration tools are used both in the collection of information from its various data sources, as well as dispensing information after it has been normalized or modeled. These tools help facilitate the input of information and utilize the data being stored within a data warehouse **.**

**Data transformation:** This feature enables functions like data cleansing, data deduplication, data validation, summarization, and more. Data transformation is needed to convert the data into a format that can be used by BI tools to extract actionable insights in a seamless manner.

**Real-time**  **analytics:** Real-time analytics features provide information in its most recent state and update users as soon as it changes. This will prevent the need to continually update data sets and simplifies the use of streaming data.

Other features of data warehouse software: [AI/ML Integration](https://www.g2.com/categories/data-warehouse/f/ai-ml-integration) and [Data Lake Integrations](https://www.g2.com/categories/data-warehouse/f/data-lake-integration).

### What are the Benefits of Data Warehouse Solutions?

Data warehouses pull data from multiple disparate sources across departments within an organization. This data flows from various CRM systems, financial systems, ERP software, and more in real time. They act as decision support systems that are designed to store historical data, further processed and transformed to make it available for decision makers to gain meaningful and valuable insights. These solutions provide a single source of truth for all the data within an organization to make data-driven decisions.

**Improved BI:** Organizations majorly use data warehouses to support their analytics and BI requirements. Data warehouses facilitate centralized data storage in a quick and easy-to-access manner which further benefits BI implementations through effective analytics and better business decision making. Thus, these solutions help gain fast, accurate, and relevant insights into their data.

**Increased return on investment (ROI):** Organizations achieve an increase in revenue due to cost savings. Deploying data warehouse solutions helps organizations consolidate data from multiple disparate sources in a specific high-quality format at one single repository, making it easily available to access and analyze better. Data warehousing solutions also help improve operational efficiency and productivity.

**Provides competitive advantage:** Data within data warehouses is pulled from multiple disparate sources from within an organization and stored in a standardized format, ready to be analyzed. This allows quick and easy access to data and helps save a lot of time in deriving insights. They enable data professionals to identify and evaluate key threats and opportunities through effective business data analysis.

**Improves operational workflow:** Data in a data warehouse is often transformed and cleaned before being loaded into it. This ensures that the data being used is good in quality and the insights generated from the data can be trusted to be accurate. This can improve the operational efficiency of businesses.

### Who Uses Data Warehouse Solutions?

Data warehousing solutions focus on data relevant to business analytics and organize and optimize it to enable efficient analysis. This software provides an easy interface for business analysts.

**Data analysts and data scientists:** These employees use data warehouses to get a centralized view of data across an organization to gain valuable insights in terms of being able to answer questions required for strategic decision making. 

#### Software Related to Data Warehouse Solutions

Related solutions that can be used together with data warehouses include:

**Databases:** Databases consist of a large family of tools used to store information digitally. There are a wide variety of databases such as [relational databases software](https://www.g2.com/categories/relational-databases), [object-oriented databases software](https://www.g2.com/categories/object-oriented-databases), and [graph databases](https://www.g2.com/categories/graph-databases). They can be used to store virtually any kind of data set, depending on their nature, but vary greatly between one another.

[ETL tools](https://www.g2.com/categories/etl-tools) **:** ETL is the most common way using which data is extracted from a data warehouse. These tools have long been used to facilitate the use of heterogeneous information sources and transform them into presentation-ready data formats.

[Big data processing and distribution software](https://www.g2.com/categories/big-data-processing-and-distribution) **:** Big data processing and distribution software often work in tandem with data warehouses to process and distribute vast sums of information prior to storage. These tools help improve the warehouse’s scalability and processing power, which improves exploration compared to ETL tools.

[Analytics platforms](https://www.g2.com/categories/analytics-platforms) **:** To implement an effective and efficient analytics system, companies require well-structured and designed data warehouses. Data warehouses can be explained as solutions for data integration which further enable reporting and analytics. Data warehouses are an essential component of analytics systems; therefore a poorly-designed data warehouse can lead to lower value from the insights generated and further impact business decision-making measures. Analytics tools are associated with data warehousing in the form of reporting and analysis of information.

### Challenges with Data Warehouse Solutions

Software solutions can come with their own set of challenges.

**On-premises data warehouse solutions:** On-premises data warehouse solutions require managing and maintenance of hardware and software infrastructure and services in-house. Organizations require dedicated teams to implement these solutions. On-premises data warehouses cannot upscale on demand. Thus, scaling up to meet changing requirements will move organizations to replace systems.

**Data quality:** Data comes in data warehouses from multiple sources within organizations. Inconsistent data like duplicates, and missing information can lead to encountering errors. Poor or error-prone data quality can result in inaccurate reports and insights, which can lead to poor decision-making.  

### How to Buy Data Warehouse Solutions

#### Requirements Gathering (RFI/RFP) for Data Warehouse Software

If a company is just starting out and looking to purchase the first data warehouse solution, or maybe an organization needs to update a legacy system--wherever a business is in its buying process, g2.com can help select the best data warehouse software for the business.

The particular business pain points might be related to unstructured and disparate data sources that must be analyzed well to use it for decision-making. If the company has amassed a lot of data, the need is to look for a solution that can help organize and structure that data to create a centralized view for analysis. Users should think about the pain points and jot them down; these should be used to help create a checklist of criteria. Additionally, the buyer must determine the number of employees who will need to use this software, as this drives the number of licenses they are likely to buy.

Taking a holistic overview of the business and identifying pain points can help the team springboard into creating a checklist of criteria. The checklist serves as a detailed guide that includes both necessary and nice-to-have features including budget, features, number of users, integrations, security requirements, cloud or on-premises solutions, and more.

Depending on the scope of the deployment, it might be helpful to produce an RFI, a one-page list with a few bullet points describing what is needed from a data warehouse software.

#### Compare Data Warehouse Solutions Products

**Create a long list**

From meeting the business functionality needs to implementation, vendor evaluations are an essential part of the software buying process. For ease of comparison after all demos are complete, it helps to prepare a consistent list of questions regarding specific needs and concerns to ask each vendor.

**Create a short list**

From the long list of vendors, it is helpful to narrow down the list of vendors and come up with a shorter list of contenders, preferably no more than three to five. With this list in hand, businesses can produce a matrix to compare the features and pricing of the various solutions.

**Conduct demos**

To ensure the comparison is thoroughgoing, the user should demo each solution on the shortlist with the same use case and datasets. This will allow the business to evaluate like for like and see how each vendor stacks up against the competition. 

#### Selection of Data Warehouse Solutions

**Choose a selection team**

Before getting started, it's crucial to create a winning team that will work together throughout the entire process, from identifying pain points to implementation. The software selection team should consist of members of the organization who have the right interest, skills, and time to participate in this process. A good starting point is to aim for three to five people who fill roles such as the main decision maker, project manager, process owner, system owner, or staffing subject matter expert, as well as a technical lead, IT administrator, or security administrator. In smaller companies, the vendor selection team may be smaller, with fewer participants multitasking and taking on more responsibilities.

**Negotiation**

Just because something is written on a company’s pricing page, does not mean it is gospel (although some companies will not budge). It is imperative to open up a conversation regarding pricing and licensing. For example, the vendor may be willing to give a discount for multi-year contracts or for recommending the product to others.

**Final decision**

After this stage, and before going all in, it is recommended to roll out a test run or pilot program to test adoption with a small sample size of users. If the tool is well used and well received, the buyer can be confident that the selection was correct. If not, it might be time to go back to the drawing board.

### What Does Data Warehouse Solutions Cost?

Data warehouse solutions are often sold as standalone products. They can be integrated with other BI and analytics tools. These typically come in two types of pricing models—flat rate and on demand._  _

### Implementation of Data Warehouse Solutions

**How are Data Warehouse Solutions Implemented?**

An organization could either decide to buy a commercial data warehouse or build an in-house data warehouse. Either way requires proper planning in terms of architecture and aligning the data warehouse project to the company goals because the end purpose is to obtain valuable insights for business leaders for strategic decision-making.

Data warehouse implementation can be done in the following ways: enterprise data warehouse, operational data store, and data mart.

**Operational data store:** An operational database (ODS) is designed to handle current operational data. The insights derived from this data primarily support the improvement of operational processes.

**Enterprise data warehouse (EDW):** This is a centralized data repository that collects enterprise data from multiple sources across the enterprise and makes it available for analysis to provide actionable insights.

**Data mart:** It can be considered as a subset of a data warehouse. It is focused on a specific division of business like sales, marketing, and finance. Data marts deliver data in small sets or partitions to provide easy and efficient access.

**Who is Responsible for Data Warehouse Solution Implementation?**

The deployment of a data warehouse requires the participation of multiple stakeholders. Some of them are as follows:

**C-suite executives:** These sets of people help users understand the long-term goals and strategies of an organization with regard to the data projects. They play a major role in scoping the data projects along with the project managers and the data team to help them understand what kind of data can be valuable to the organization for decision making. 

**Project managers:** They are responsible for overseeing the overall project in terms of budget, schedules, deadlines, and project roadblocks. The project manager is assigned with the task to communicate the progress of the project to the senior management.

**IT team:** These teams consist of business analysts, technical architects, ETL experts, and specialists. This team plays a role in supporting the data projects helping execute activities like developing the data warehouse, connecting data sources, executing ETL processes, and more. They may be required to support the system if it’s an on-premises deployment.

**What Does the Implementation Process Look Like for Data Warehouse Solutions?**

The implementation process of a data warehouse solution can be broken down into the following steps:

**Gathering and defining requirements:** This step involves understanding the organization’s long-term business strategies and goals. It also covers various other criteria in terms of the kind of analysis and reporting required, as well as hardware, software, testing, implementation, and training of users. This step involves multiple stakeholders starting from the C-suite decisions, data, and analytics team, IT support, and the data governance team.

**Data warehouse environment:** As the next step, users must decide which deployment model is suitable: on-premises, public or private cloud, or hybrid cloud. Public cloud is considered one of the least expensive models as the cloud provider takes care of managing and maintenance of the infrastructure hardware requirements.

**Data modeling:** One of the crucial steps in data warehouse implementation is deciding on the data model. Every data source has a specific data scheme, picking up a single schema that is a fit for all is required. 

**Connecting data sources through ETL process:** This step includes data extraction from multiple disparate sources, transforming it through converting the data from the source schema to the assigned destination schema and further loading it into the data warehouses. Transformation of the data also includes a couple of other actions that can be performed on the dataset like validation, enrichment, and other data health measures.

**Integration to BI and analytics tools:** Once a data warehouse system is set up, the next step involves integrating the BI tool being used by the organization with the warehouse data. This facilitates reporting and analytics which leads to delivering faster and easy insights for better decision making.

**Testing and validating the system:** This step includes the end-to-end testing of the entire data warehouse system. The system can be tested on various sets of parameters like data quality and integrity checks, the performance of the system, and analyzing whether it fulfills the end-user requirements in terms of reporting and analytics.

### Data Warehouse Solutions Trends

**Shifting to cloud data warehousing solutions**

Organizations are increasingly adopting cloud data warehouses to achieve improved scalability and performance. This shift helps them focus more on managing their business activities than managing a server block. Cloud data warehouse solutions also let organizations access easy real-time data from multiple sources, enabling them to gain better insights quickly. Companies can also achieve cost-effectiveness with data warehouses deployed on the cloud because it’s less expensive to scale a cloud data warehouse than one deployed on-premises. Also, buyers end up paying for the resources that they use, which further improves operational efficiency.

**Moving towards DWaaS**

Organizations are moving towards data warehouse as a service (DWaaS) as it lets buyers take advantage of eliminating hardware and software procurement, configuration, and maintenance work as a third party is responsible for these. Starting from data warehouse administration to setting up a data warehouse team, the providers are responsible for it.