Amazon
Web Services
Microsoft Azure
Google Cloud PlatformDatabricks documentation archive
Important
This documentation has been retired and might not be updated. The products, services, or technologies mentioned in this content are no longer supported.
In this archive, you can find earlier versions of documentation for Databricks products, features, APIs, and workflows.
Dev tools
- Manage libraries with
%condacommands (legacy) - Explore and create tables in DBFS
- Transactional writes to cloud storage with DBIO
- Koalas
- Legacy UniForm IcebergCompatV1
- Workspace libraries (legacy)
- Databricks CLI (legacy)
- What is dbx by Databricks Labs?
- dbutils.library
- Migrate to Spark 3.x
- VScode with Git folders
Machine learning and AI
- Share feature tables across workspaces (legacy)
- MLeap ML model export
- Train a PySpark model and save in MLeap format
- Deploy MLeap model on SageMaker
- Model serving (legacy)
- Serverless Real-Time Inference (preview)
- Optimized LLM serving
- Set up and considerations for
ai_generate_text() - Analyze customer reviews with
ai_generate_text()and OpenAI
Storage
- End-of-life for legacy workspaces
- Amazon S3 source with Amazon SQS (legacy)
- Azure Blob storage file source with Azure Queue Storage (legacy)
- Azure Cosmos DB
- Connecting Databricks and Azure Synapse with PolyBase (legacy)
- Neo4j
- Read and write XML data using the
spark-xmllibrary - Accessing Azure Data Lake Storage Gen1 from Databricks
- Configure Delta storage credentials
- Connect to Azure Blob Storage with WASB (legacy)
