Kafka streaming vs gRPC batching time series data

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I would like some technology thoughts on a comparison use case. we process million of data points / sec in time series data. We have a ingestion endpoint service which hands it over to a compute intensive service which indices these points. We do gRPC hand off today. Some folks in the team want to move to async streaming processing model with Kafka which give immediate fault tolerance etc. Some team members claim adding a messaging layer adds latency to affect the processing of indices. What are trade off there?

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