The Lakehouse Platform combines the best elements of data lakes and data warehouses — delivering data management and performance typically found in data warehouses with the low-cost, flexible object stores offered by data lakes. This unified platform simplifies your data architecture by eliminating the data silos that traditionally separate analytics, data science and machine learning. It’s built on open source and open standards to maximize flexibility. And, its native collaborative capabilities accelerate your ability to work across teams and innovate faster.

Databricks’ Machine Learning platform lets data science teams build AI models based on the AutoML framework, and empowers ML teams to prepare and process data, streamlines cross-team collaboration, and standardizes the full lifecycle from experimentation to production. With the Machine Learning platform users can simplify all aspects of data for ML, automate experiment tracking and governance, manage the full model lifecycle with the Model Registry, and deploy ML models at scale and low latency.

Databricks SQL allows customers to operate a multi-cloud lakehouse architecture that provides data warehousing performance at data lake economics.