Amazon SageMaker Canvas now supports additional data connectors with JDBC

Amazon SageMaker Canvas now supports eight new JDBC connectors for Salesforce, Databricks, SQL Server, MySQL, PostgreSQL, MariaDB, Amazon RDS, and Amazon Aurora. Additionally, importing data from Snowflake without a storage intermediary and OAuth 2.0 connectivity for Salesforce and Snowflake are now supported, enabling customers to seamlessly import data from a variety of sources. SageMaker Canvas is a visual interface that empowers business analysts and citizen data scientists to generate accurate ML predictions without ML expertise.

Data ingestion is often the first step in building high-quality ML models. When data connectors to mission-critical systems are not available, the process of centralizing data is slow and frustrating because users must transfer data to intermediary sources before continuing their ML journey. This adds friction and may cause users to leave crucial data out of their models, which may limit the value they receive from ML.

Canvas now provides more flexibility and choice to import data from a range of sources. With JDBC support, Canvas provides increased flexibility to import data from sources such as Salesforce, Databricks, SQL Server, MySQL, PostgreSQL, MariaDB, Amazon RDS, and Amazon Aurora. Additionally, administrators can now configure OAuth 2.0 connections to Salesforce and Snowflake, enabling users to use their own credentials to import data from different sources. For example, users can import marketing data from Salesforce or sales records from SQL Server and then join that data with other sources, build ML models, and generate predictions without writing any code.

Support for these new data connectors is available in all AWS regions where Canvas is available. To get started importing data from these new sources, follow the SageMaker Canvas documentation.