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Decodable Platform Now Ships With ‘Change Data Capture’ Connectors

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Decodable, the real-time data engineering company, recently announced three new capabilities in the Decodable platform at Current 2022, the next generation of the Kafka Summit. Decodable is a powerful and easy-to-use stream processing platform, ideal for unlocking the full potential of Kafka by moving data anywhere, with real-time speed and transformed to match the needs of its destination.

The Decodable platform now ships with turnkey CDC (change data capture) connectors that effectively convert relational database tables into real-time streams of records describing every change to the table (insert, update, delete, etc.) as an event. The connector will initially treat every table row as an insert event to bulk transfer the table. Subsequent changes to the table trigger more records describing each change as an event.

CDC Connectors for MySQL and PostgreSQL are already included in the Decodable platform and ready for cloud implementations in popular services like Amazon Cloud RDS or Google Cloud SQL. Connectors for Oracle, MSSQL, Snowflake and more are coming soon.

The Decodable platform now includes the capability of multi-way streaming table joins for large data sets. This feature is based on Apache Flink and includes custom optimizations by Decodable. Whereas other technologies may provide 2-way streaming table joins, Decodable has successfully executed 14-way streaming joins, as proven by customers in production who are processing terabytes of data without dropping a beat.

The ability to join multiple change streams is only useful if you can perform processing on the resultant data stream. It turns out that processing individual change records emanating from multiple streams is difficult to get right and that difficulty increases exponentially with each additional streaming data source in the join.

Decodable eliminates this challenge by abstracting change records back into their original tables— so you write industry standard SQL as if you were processing the original table and never see the underlying change records. This massively reduces time to value and eliminates human error introduced by processing change records directly.

Decodable has also added features to strengthen the platform’s ease of use and scalability: previewing data in change streams as well as large-scale efficiency.