Accelerate the agentic enterprise

The platform is built for both business and technical users across data and AI teams, not just specialized engineers. Business users get guided insights, automated workflows and simple agent creation through natural language, while technical users get a partner to write code, build apps and handle engineering operations automatically. Because it unifies data engineering, data science and machine learning in one workspace, it suits organizations that want one platform for teams that previously worked across several separate tools. Databricks is trusted by data and AI teams worldwide who are turning data into analytics, applications and agents.

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• Get instant access to the Databricks Data + AI Platform
• Ingest and prepare data with automated workflows
• Build high-quality apps and agents
• Query your data with common language

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Databricks offers the only platform built from the ground up for data and AI together. Unlike legacy tools that bolt AI onto analytics after the fact, the Databricks Data + AI Platform was built to bring together data ingestion, transformation, analytics and machine learning in one place — eliminating the need for teams to stitch together many different platforms. This represents a reversal of the past decade's trend toward specialized tools. The Databricks Data + AI Platform is designed around the thesis that unification is the competitive advantage — one copy of data, one processing engine, one governance model across all clouds and all workloads.

Lakehouse architecture brings together the flexibility of a data lake and the reliability of a data warehouse. Delta Lake enforces data quality rules, supports ACID transactions to prevent corruption and offers time travel — the ability to query data as it existed at any prior point.

Databricks lets teams build, evaluate and govern AI agents on one platform instead of stitching together separate development and oversight tools. Agent Bricks offers multi-harness development, so teams can build agents using any model, framework or agent — custom or third-party — then evaluate, deploy and optimize them on one governed foundation. Unity Catalog manages data and AI assets with consistent permissions, lineage and auditing, while Unity Gateway governs AI usage, controlling access, spend and observability across agents, tools, models and MCPs. Agents are also grounded in enterprise context through Genie Ontology, which continuously updates by learning from actual organizational usage.

With open formats like Delta Lake and Apache Iceberg™, data is portable: you can query it from Databricks today, Spark tomorrow and Trino next year and never move a byte. Customers in competitive evaluations consistently cite openness as one of their primary deciding factors — and Unity Catalog, as an open governance layer, is cited as a unique capability that competitors haven't matched.