As an increasing number of users leverage the Ascend platform for their data engineering projects, we begin to see new patterns and exciting new use cases emerge. A while back, we noticed a strong need to quickly prototype Dataflow logic before deploying as full fledged transforms, which led to the creation of Queryable Dataflows. Soon after, we noticed a number of users wanting access to that same data found in the intermediate Dataflow stages, but via object/blob store interfaces, which led to the creation of the Structured Data Lake. And, in our partnership with Looker, we’ve seen the incredible need for BI users to have easy access to powerful ETL capabilities. As nearly all BI tools in the market today support JDBC connectors, and we’ve found many of these users interested in accessing the data within Dataflows, we thought we’d take things one step further.
Today we’re excited to announce the general availability of our JDBC/ODBC Dataflow connector. This feature leverages the same intelligent persistence layer that backs Queryable Dataflows and Structured Data Lakes, and joins it (pun intended) with the SparkSQL Thrift JDBC/ODBC Server to provide the ability to directly access and query your Dataflows from your favorite environment, whether it is a BI tool like Looker, or your favorite SQL workbench.
Accessing the feature is easy. Simply create a Service Account, set the appropriate permissions, and use the username and password provided. No additional configuration, provisioning, or tinkering required!
Ready to start with JDBC/ODBC Dataflow Connectors? Sign up for a free trial and start building! Want to learn more about this feature and the other parts of the Ascend Unified Data Engineering platform? Schedule a live demo with one of our data engineers. Have a favorite function you’d like to see us add support for? Join us in Slack (#feature-requests) and let us know — we’d love to hear from you!
