Databricks documentation

The Databricks Unified Data Analytics Platform, from the original creators of Apache Spark, enables data teams to collaborate in order to solve some of the world’s toughest problems.

Databricks excels at enabling data scientists, data engineers, and data analysts to work together on uses cases like:

• Applying advanced analytics for machine learning and graph processing at scale
• Using deep learning for harnessing the power of unstructured data such for AI, image interpretation, automatic translation, natural language processing, and more
• Making data warehousing fast, simple, and scalable
• Proactively detecting threats with data science and AI
• Analyzing high-velocity sensor and time-series IoT data in real-time
• Making GDPR data subject requests easy to execute

This documentation site provides how-to guidance and reference information for Databricks SQL Analytics and Databricks Workspace.

• Getting started with Databricks

• Databricks SQL Analytics guide
  • Get started
  • User guide
  • Administration guide
  • Security guide
  • API reference
  • SQL reference
  • Release notes

• Databricks Workspace guide
  • Get started with Databricks Workspace
  • Best practices
  • Language roadmaps
  • User guide
  • Data guide
  • Delta Lake and Delta Engine guide
  • Machine learning and deep learning guide
  • MLflow guide
  • Genomics guide
  • Administration guide
  • API reference
  • Release notes
• Resources
  • Platform release process
  • Supported browsers
  • Support
  • Ideas Portal
  • Status Page