Kafka evolves as a platform for real time data streaming, analytics, and event processing. For enterprise customers the challenge is to let data originating on IBM z flow to Kafka. Popular options are Kafka APIs, MQ, data replication. Only data replication offers mechanisms to let data flow to Kafka without to change existing applications.
IBM supports data replication to Kafka with CDC technology. We have a significant Q Replication footprint already, running Q Replication on dozens of systems for thousands of tables. The effort of introducing another data replication technology with the desired degree of monitoring and automation just because Q Replication does not support Kafka targets would be significant and should be avoided. We consider that the Q Rep operational model would fit very well to support Kafka targets.
|Who would benefit from this IDEA?||All enterprise customers with existing Q Replication footprint. The more systems and the more tables replicated with Q Rep today, the bigger the benefit.|
How should it work?
The desired solution should be able to read Q Rep's compact message format, convert the data to unicode, and feed a Kafka producer to store the replicated data as Kafka messages. One topic per replicated table.
Especially for existing Q Rep enterprise customers the benefit would be high.
|Priority Justification||Established procedures could be used to manage the data replication to Kafka, MIPS could be saved significantly, because no additional log reader has to be run on the source platform, admin manpower would be saved to set up and monitor the solution.|
|Client Name||Katrin Weiher|
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