Introduction to Databricks

Databricks is a cloud-based collaborative data science, data engineering, and data analytics platform that combines the best of data warehouses and data lakes into a lakehouse architecture.

These articles can help you understand the key concepts and features of the Databricks platform

• Concepts

  Learn fundamental Databricks concepts such as workspaces, data objects, clusters, machine learning models, and access.

• Architecture

  Get a high-level overview of Databricks and its enterprise architecture.

• Language-specific overviews

  Learn how to use Python, SQL, R, and Scala to perform collaborative data science, data engineering, and data analysis in Databricks.

• Supported clouds and regions

  Learn about the regions supported by Databricks.

• Databricks datasets

  Databricks includes a variety of datasets mounted to the Databricks File System (DBFS) that you can use to test your queries and models. These datasets are used in examples throughout the documentation.

• Apache Spark

  New to Apache Spark? Write your first Apache Spark application, create a DataFrame and Dataset, do some basic machine learning, and learn how to handle streaming data.

• Delta Lake

  Learn about the Delta Lake storage layer and optimizations available with Delta Lake on Databricks.

• Integrations

  Learn how to connect Databricks to data sources, BI tools, and developer tools.

• Support

  Learn about Databricks support options.

• Free training

  Try out our self-paced training, free to Databricks customers.