We are a source system and we have a couple of downstream systems which would require our data for their needs, currently we are publishing events onto Kafka topics as and when there is a change in source system for them to consume and make changes to their tables (all delta updates)
Our downstream systems is currently accessing our database directly sometimes to make complete refresh of their tables on demand basis once in a while to make sure data is in sync apart from subscribing to Kafka topics, as you know we always need a data refresh sometimes when we feel data is out of sync for some reason.
We are planning to stop giving access to our database directly, how can we achieve this ? Is there a way that consumers request us their data needs by any triggers like passing request to us and we can publish the stream of data for them to consume on their end and they sync the tables or get the bulk data into their memory to perform some tasks based on their needs.
We currently have written RESTful APIs to provide data based on the requests, but we are exposing small data volumes as I think APIs we only send smaller volumes of data, but it won't work when we want to send millions of data to consumers and I believe only way is to stream data on Kafka, but with Kafka how can we respond to the request from consumers and only pump that specific data on to Kafka topics for them to consume ?
You have the option of setting the retention policy on any topic to keep messages forever with:
retention.ms: -1
In that case you could store the entire change log in the same manner that you currently are. Then if a consumer needs to re-materialize the entire history, they can start with the first offset and go from there without you having to produce a specialized dataset.