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.