Datacoral Connector: JDBC

Datacoral Connector: JDBC

Datacoral is excited to announce the release of our JDBC connector for ingesting data from any database into any data warehouse through the standardized JDBC interface.

While Datacoral already supported ingesting data from multiple databases (such as PostgreSQL and MySQL), we wanted to open up our data integration platform for all databases and SaaS tools based sources that provide data access through JDBC. So, with our JDBC connector, our customers can easily replicate data from databases like Oracle and Microsoft SQL Server and services like NetSuite and SAP By Design that offer JDBC drivers all the while ensuring that their data never leaves their AWS account.

And like all of our connectors, the JDBC connector automatically maps the source table schemas to warehouse schemas and figures out the best way to sync data from the source databases to the destination warehouse based on both the size and structure of the source tables. For example, the connector can automatically take advantage of any primary keys or timestamp columns in the tables to efficiently sync data incrementally. In addition, you will have the ability to configure the connector to precisely define the data being fetched – via column lists as well as by running arbitrary queries in the source database.

Column lists can be used to filter out sensitive columns that should not be visible during analysis. Arbitrary queries can be used to run complex transformations directly at the source before the data is synced to the warehouse.

Datacoral supports the following SQL dialects out-of-the-box:

  1. PostgreSQL
  2. MySQL
  3. Microsoft SQL Server
  4. Open Access and all services that offer Open Access JDBC drivers
  5. Oracle

You can bring in your own custom JDBC drivers for their data sources and use the arbitrary source query feature to use any SQL dialect supported by your JDBC driver.

These capabilities allow data teams to flexibly and reliably replicate the data they need to the data warehouses of their choice, while maintaining privacy and security in the cloud and complying with GDPR and CCPA.

We are excited to see the different ways in which our customers use this connector to reliable replicate their data into their data warehouse. For complete details, check out our documentation page for the JDBC connector. If you have any questions about replicating data from different databases, drop us a note at



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