Lakehouse for companies born in the cloud
Build and scale data, analytics and AI capabilities faster on one high-performing data platform
You’re laser focused on overcoming scalability challenges with data. The faster you grow, the more complex your data becomes — and the more urgent it becomes to innovate faster. The Databricks Lakehouse Platform is the simple, cost-efficient approach to data, analytics and AI — making thousands of digital native businesses more productive.
Innovate with open source flexibility
Build scalable data workloads
Access data insights faster
Develop next-gen apps with ML
Getting started with Databricks
Get started
Build your skills
Optimize costs
Technical support
Solutions architectures for digital native businesses
High-performing, scalable ETL pipelines
Build an end-to-end data engineering and ETL platform that lets you focus on delivering valuable insights on any cloud. No more building and maintaining pipelines or running ETL workloads.
Leverage production-ready tools including Delta Live Tables, Unity Catalog and Workflows.
Enjoy robust Git integration, orchestration and data quality controls.
Unify batch and streaming operations on a simplified architecture, and streamline data pipeline development and testing.
Ensure data quality and enhanced data skipping with Delta Lake — an open source file protocol usable by Apache Spark, Trino, Presto, Flink and more.
SQL analytics and data warehousing
Easily ingest, transform and query all your data in one place to deliver real-time business insights faster.
Run all your SQL and BI applications at scale with up to 12x better price/performance. Ensure data governance and security.
Handle high concurrency with fully managed load balancing and scaling of compute resources.
Leverage open formats and APIs, and the ingestion, transformation and BI tools of your choice with custom-built connectors.
Reduce resource management overhead with serverless compute.
Innovative machine learning
Accelerate ML and data science by improving productivity and collaboration on the lakehouse.
Leverage collaboration tools and options for glass-box AutoML.
Prepare, process and manage data and features in a self-service manner — as well as manage models — and with a hosted Feature Store.
Standardize the ML lifecycle from experimentation to production through MLflow to track model parameter, metrics and iterations over time.
Deploy models in a batch or with serverless real-time REST endpoints.
Next-generation businesses built on Databricks
Blog
Customer Story
Partners and programs
Discover and integrate your favorite data and AI tools and services directly from the Databricks platform
Industry solutions
Next-generation industry leaders are building their data analytics and AI solutions with Databricks
