Batch and streaming pipelines
Lakeflow combines data ingestion, transformation and orchestration for building ETL pipelines at scale.
A unified data and AI platform for enterprise analytics, pipelines, apps and agents.
Databricks is a cloud platform that brings data engineering, data warehousing, business intelligence, AI and operational databases onto one governed foundation. It supports both analytical and transactional workloads, giving organizations a shared environment for preparing data, analyzing it and building applications that use it.
Its Data + AI Platform includes Lakeflow for pipelines, Lakehouse for warehousing, AI/BI for analytics, Agent Bricks for AI agents and Lakebase for Postgres applications. Unity Catalog provides governance across data and AI assets. The lakehouse architecture combines flexible data lake storage with warehouse capabilities, including ACID transactions, schema enforcement and SQL queries on open formats such as Delta Lake.
Lakeflow combines data ingestion, transformation and orchestration for building ETL pipelines at scale.
AI/BI supports natural language dashboard creation. Genie answers plain-language questions about enterprise data with text summaries, tables and visualizations, without requiring SQL or coding.
Lakebase integrates Postgres with the lakehouse and synchronizes transactional data with analytics and AI systems without custom ETL pipelines.
Agent Bricks supports building production AI agents grounded in an organization's own data.
Unity Catalog provides a shared governance layer for data, models, dashboards and agents. Unity Gateway adds access management, cost control, observability and guardrails across enterprise AI.
Lakehouse provides serverless warehousing on open lake data, with governance and AI capabilities built into the platform.
Data engineering teams can ingest and transform records from operational systems into datasets for BI, reporting and analysis, using batch or streaming workflows.
Business users can ask Genie questions such as how their sales pipeline is performing and review the resulting summaries, tables and visualizations.
Application teams can run transactional workloads in Lakebase while making that data available to analytics and AI systems on the same platform.
Teams managing agents, tools and models can use a common governance layer to monitor access, spending and activity across their AI environment.
Databricks offers pay-as-you-go pricing with no upfront costs and per-second usage granularity. Charges depend on the products and compute used; storage, networking, region and cloud provider also affect costs. Committed use contracts offer discounts. Microsoft sets Azure Databricks pricing.
The trial provides access to the Data + AI Platform and lets you invite collaborators. Some trials include service credits, with eligibility, amounts and expiration determined after account creation. If you use your own cloud account, your cloud provider still charges for resources used during the trial.
You are automatically subscribed to the plan used during the trial. Continuing may require a valid payment method, and you can cancel the subscription at any time.
Databricks provides platform documentation for AWS, Microsoft Azure and Google Cloud. Product and infrastructure prices can vary by cloud provider and geographic region.
Databricks offers technical support, documentation and a customer Help Center for billing and technical issues. Training includes instructor-led and self-paced courses, along with developer certification.
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