Customer Satisfaction
5.4/10
5.4
User Experience
5.8/10
5.8
Technical Foundation
7.7/10
7.7
Business Value
5.4/10
5.4

Databricks Data Intelligence Platform

What is Databricks Data Intelligence Platform?

End-to-end platform solution for data engineering & data science based on a further development of Apache Spark technology.

Data Management & Storage
● Databases & Access Engines
● Data Intelligence, Data Catalogs and Marketplaces
● Data Operations
● Data Pipelining and Data Quality

= covered

About Databricks Data Intelligence Platform

Self-description of the vendor

No vendor self-description available
References
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Partners
No data available

Databricks Data Intelligence Platform BARC Review & Rating

Provider and product description

Databricks, founded in 2013 and headquartered in San Francisco, focuses on simplifying and democratizing data and AI solutions. With offices worldwide, the company delivers a data platform designed to engage data and AI teams to solve complex enterprise challenges.

The vendor’s Data Intelligence Platform is built on an open lakehouse architecture. The platform unifies data and governance, integrating AI models tailored to each organization. It allows users in an organization to access data insights through automation and natural language, while technical teams can easily build and deploy secure data apps and data products.

Databricks is built on top of key technologies like Delta Lake, Apache Spark and MLflow. These open-source innovations allow for efficient and scalable data management. The platform uses Delta Sharing, an open protocol for secure data sharing across applications, minimizing data replication and enhancing data governance through centralized solutions for auditing and tracking data usage.

Through its Mosaic product, Databricks simplifies AI deployment, governance and evaluation. With integrated tools such as Vector Search, RAG (retrieval augmented generation), model serving and training features, it supports comprehensive AI workflows.

The platform supports real-time data processing via Delta Live Tables, workflows, data streaming and Unity Catalog. These features make it adaptable for various data-intensive applications.

Databricks has cultivated a strong partner ecosystem, with over 1,200 global partnerships, including cloud providers, ISVs and consulting firms.

Strengths and challenges of Databricks Data Intelligence Platform

BARC’s viewpoint on the product’s strengths and challenges.

Strengths
  • The top three use cases for Databricks are cloud data warehousing/BI, data integration and data mesh/data product deveolpment.
  • Platform performance and fit to future technology landscapes are top reasons customers select Databricks.
  • Databricks’ technical foundation ranked highly for Extensibility, Scalability and Connectivity in the Cloud Data Platforms peer group.
Challenges
  • The complexity of the platform and user know-how is ranked somewhat higher than peers within the same group.
  • Pricing models and ongoing cost of operation rank higher than the category average with Databricks.
  • In the Business Value KPI category, Databricks ranked last for Project Length amongst its peers’ solutions.
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Databricks Data Intelligence Platform User Reviews & Experiences

The information contained in this section is based on user feedback and actual experience with Databricks Data Intelligence Platform.

The information and figures are largely drawn from BARC’s The BI & Analytics Survey, The Planning Survey, The Financial Consolidation Survey and The Data Management Survey. You can find out more about these surveys by clicking on the relevant links.

Who uses Databricks Data Intelligence Platform in a data management context and how

Why users buy Databricks Data Intelligence Platform and what problems they have using it

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Full user reviews and KPI results for Databricks Data Intelligence Platform

All key figures for Databricks Data Intelligence Platform at a glance.

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Individual user reviews for Databricks Data Intelligence Platform

Role
Enterprise architect
Number of employees
More than 2.500
Industry
Transportation and logistics
Source
BARC Marketing, The Data Management Survey 25, 03/2024
What do you like best?

Flexibilität in der Programmiersprache. Trennung von Storage und Compute.

What do you like least/what could be improved?

Komplexität insbesondere in Bezug auf den Unity Catalogue.

What key advice would you give to other companies looking to introduce/use the product?

Es braucht ein übergreifendes Konzept für die Verwendung (z.B. Data Lakehouse, Medaillon Architecture, etc.).

How would you sum up your experience?

Zum Einsatz als zentrale Datenmanagement Plattform geeignet.

Role
Consultant
Number of employees
More than 2.500
Industry
Consulting
Source
BARC Panel, The Data Management Survey 25, 03/2024
What do you like best?

Unified data platform: Databricks can handle both structured and unstructured data, which is crucial in healthcare where patient information comes in various formats and this simplifies data management.

What do you like least/what could be improved?

Data integration: While Databricks can handle various data types, integrating data from disparate healthcare systems can still be complex and require additional tools or expertise.

What key advice would you give to other companies looking to introduce/use the product?

Ensure you have the resources appropriately trained to leverage its capabilities and understand aligning your use cases to the strengths of the platform.

How would you sum up your experience?

The alignment with Microsoft Azure is second to none and this is the heart of my client's cloud architecture. This makes Databricks a critical platform and Databricks continues to deliver on needed features and functions.

Role
Enterprise architect
Number of employees
More than 2.500
Industry
Healthcare
Source
BARC Panel, The Data Management Survey 25, 04/2024
What do you like best?

Great, performant, stable tool. We switched over from Cloudera's Hive/Impala and it was a huge improvement.

What do you like least/what could be improved?

The price. It is expensive and we need to keep a close eye on cloud costs.

What key advice would you give to other companies looking to introduce/use the product?

Small POCs, validate its true cost, invest time in optimizing data-models and/or queries. Every cent spent in query optimization saves $$ on the medium long term.

How would you sum up your experience?

Expensive but love it.

Role
Data engineer/Data manager
Number of employees
More than 2.500
Industry
Transportation and logistics
Source
BARC Panel, The Data Management Survey 25, 02/2024
What do you like best?

Einfachheit der Administration.

What do you like least/what could be improved?

Integration mit anderen Services ist aufwendig.

What key advice would you give to other companies looking to introduce/use the product?

Es gibt einen Unterschied zwischen Marketing und der sinnvollen Nutzung.

How would you sum up your experience?

Die Nutzung von neuen Features vorsichtig einführen.

Role
Consultant
Number of employees
More than 2.500
Industry
Utilities
Source
BARC Panel, The Data Management Survey 25, 03/2024
What do you like best?

The Spark SQL Engines makes it easy for SQL Developers to work with the platform.

What do you like least/what could be improved?

-

What key advice would you give to other companies looking to introduce/use the product?

-

How would you sum up your experience?

It's a powerful ecosystem for data & analytics.

Survey Information
Number of reviews for Databricks Data Intelligence Platform
24
Reviewed versions
53 percent Azure, 24 percent version 13.3, 12 percent version 12, 12 percent version 21c
Peer groups in the survey
Cloud Data Platforms, Data Product Engineering, Data Product Engineering (Big Players), Data Intelligence Platforms & Marketplaces, Data Intelligence Platforms (Large Scenarios), Data Intelligence Platforms (Big Players)
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