collaborative environment
A secure, collaborative environment for organizing notebooks, clusters, jobs, dashboards, libraries, and experiments.
code + markdown cells
Interactive documents that combine runnable code, visualizations, and Markdown text for analysis, engineering, and collaboration.
driver + worker nodes
Compute engines that run workloads using a driver node to coordinate work and worker nodes to process data in parallel.
Apache Spark builds
A Databricks-optimized Apache Spark environment with performance improvements, libraries, and versioned runtime support.
workflow automation
Managed workflows that schedule, coordinate, and automate repeatable tasks such as ETL pipelines, ML training, and refresh jobs.
ACID transactions
An open-source storage framework that adds ACID transactions, versioning, scalable metadata, and batch/streaming support to data lakes.
Premium tier analytics
A SQL-based analytics experience for querying lakehouse data, building dashboards, and connecting BI tools.
serverless · pro · classic
Scalable compute resources optimized for SQL queries and BI workloads, available as serverless, pro, or classic options.
ML lifecycle
An open-source platform for managing the machine learning lifecycle, including experiments, reproducibility, models, and deployment.