Connect to external systems

Azure Databricks provides built-in integrations to many cloud-native data systems, as well as extensible JDBC support to connect to other data systems.

Соединители, описанные в этом разделе, в основном сосредоточены на настройке подключения к одной таблице во внешней системе данных. You can use some of these drivers to write data back to external systems as well.

Для подключений к данным только для чтения Databricks рекомендует использовать федеральную систему Lakehouse, которая позволяет синхронизировать целые базы данных с Azure Databricks из внешних систем и находится под управлением Unity Catalog. См. статью "Что такое Федерация Lakehouse?".

Partner Connect also provides integrations to many popular enterprise data systems. Many Partner Connect solutions not only connect to data sources, but also facilitate easy ETL to keep data in your lakehouse fresh. См. статью Что такое Databricks Partner Connect?.

What data sources connect to Azure Databricks with JDBC?

You can use JDBC to connect with many data sources. Databricks Runtime includes drivers for a number of JDBC databases, but you might need to install a driver or different driver version to connect to your preferred database. Supported databases include the following:

• Query PostgreSQL with Azure Databricks
• Query MySQL with Azure Databricks
• Query MariaDB with Azure Databricks
• Query SQL Server with Azure Databricks
• Use the Databricks connector to connect to another Databricks workspace

What data services does Azure Databricks integrate with?

Следующие службы данных требуют настройки параметров подключения, учетных данных безопасности и параметров сети. You might need administrator or power user privileges in your Azure account or Azure Databricks workspace. Some also require that you create an Azure Databricks library and install it in a cluster:

• Query data in Azure Synapse Analytics
• MongoDB
• Cassandra
• Couchbase.
• ElasticSearch
• Read and write data from Snowflake
• Google BigQuery