Databricks is a cloud platform that simplifies collecting, processing, and analyzing large volumes of data while providing built-in tools for machine learning and generative AI.

Born in 2013 out of UC Berkeley's AMPLab-the creators of Apache Spark-Databricks quickly became the core of a new architecture: the "lakehouse." The lakehouse combines the flexibility of data lakes with the structure of databases, enabling both advanced analytics and AI. The platform covers everything from ETL pipelines and real-time streaming to model training, deployment, and governance in a unified interface.

It is tightly integrated with technologies such as Delta Lake, MLflow, and MosaicAI, and is widely used across major cloud providers like AWS, Azure, and Google Cloud. Databricks has open-sourced parts of its technology-benefiting the wider data engineering ecosystem-and has released its own open-source LLMs such as DBRX, all with the goal of simplifying and accelerating the entire data‑to‑AI journey for organizations.