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In the 2016 release Microsoft embedded R and Python, as well as added support for JSON and the inclusion of the Polybase feature, which allowed for querying or importing data from sources including Hadoop, Azure Data Lake Store and Azure Blob Storage. SQL Server 2019 sees an expansion of the external sources open to Polybase to include relational and non-relational data sources such as Oracle, SAP HANA, DB2, Postgres, MySQL, mongoDB, CosmosDB, Teradata and Spark. With Big Data Clusters you can run Spark jobs to analyze both structured and non-structured data, develop and train models from data hosted virtually anywhere using Spark ML or SQL Server Machine Learning Services, and subsequently query the data from anywhere using notebooks in Azure Data Studio.