Azure Cosmos DB is Microsoft’s globally distributed, multi-model database. Azure Cosmos DB enables you to elastically and independently scale throughput and storage across any number of Azure’s geographic regions. It offers throughput, latency, availability, and consistency guarantees with comprehensive service level agreements (SLAs). Azure Cosmos DB provides APIs for the following data models, with SDKs available in multiple languages:
- SQL API
- MongoDB API
- Cassandra API
- Graph (Gremlin) API
- Table API
This article explains how to read data from and write data to Azure Cosmos DB using Databricks. For more the most up-to-date details about Azure Cosmos DB, see Accelerate big data analytics by using the Apache Spark to Azure Cosmos DB connector.
You cannot access this data source from a cluster running Databricks Runtime 7.0 or above because an Azure Cosmos DB connector that supports Apache Spark 3.0 is not available.
The following Scala notebook provides a simple example of how to write data to Cosmos DB and read data from Cosmos DB. See the Azure Cosmos DB Spark Connector project for detailed documentation. The Azure Cosmos DB Spark Connector User Guide, developed by Microsoft, also shows how to use this connector in Python.