What is Databricks?
Databricks describes a lakehouse architecture connecting processing and analytics over shared data. The managed platform serves several workloads, but compute choices, storage design and governance remain customer decisions. An open source foundation does not mean that the managed service is free.
Read the full overview
Official sources checked 27 September 2026: lakehouse architecture, platform scope.
Key capabilities
- Data engineering workflows
- SQL and analytical workloads
- Machine learning on the platform
Map the path from source to governed table to consumer. Define schema ownership, compute policies and retention before migrating a major workload.
Shortlist Databricks when engineering and analytics need common datasets. Prototype ingestion, transformation and production queries, then inspect permissions and cost attribution.
A shared platform can reduce duplicated plumbing while concentrating spend and access decisions. Make both visible in the pilot.
Technical details
- Access
- See vendor
- Source model
- Other license
- Founded
- 2013
- Headquarters
- San Francisco, USA
- Pricing model
- Paid
- API
- Available
- Website
- www.databricks.com ↗
Official resources
What to verify for your environment
Start from the users, systems and operating responsibilities the tool needs to support.
- Confirm current features, licensing and support terms with the publisher.
- Validate deployment, data location, access control, backup and recovery requirements.
- Test integrations, export paths and a representative operational workflow before committing.
ITHub profiles are discovery summaries. Read how product information is presented or report a correction.
Reviews of Databricks
No published reviews yet.
Loading review form…
