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Close the gap between the semantics of KTables in streams and tables in relational databases. It is common practice to capture changes as they are made to tables in a RDBMS into Kafka topics (JDBC-connect, Debezium, Maxwell). These entities typically have multiple one-to-many relationship. Usually RDBMSs offer good support to resolve this relationship with a join. Streams falls short here and the workaround (group by - join - lateral view) is not well supported as well and is not in line with the idea of record based processing.

This KIP makes relational data liberated by connection mechanisms far easier for teams to use, smoothing a transition to natively-built event-driven services.

Features

1. Perform KTable-to-KTable updates from both sides of the join
2. Resolves out-of-order processing due to foreignKey changes
3. Scalable as per normal joins

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