Kappa Architecture - SPA

Kappa Architecture

• The idea is to handle both real-time data processing and continuous reprocessing in a single

stream processing engine.

• This requires that the incoming data stream can be replayed (very quickly), either in its entirety

or from a specific position.

• If there are any code changes, then a second stream process would replay all previous data

through the latest real-time engine and replace the data stored in the serving layer.

• This architecture attempts to simplify by only keeping one code base rather than manage one

for each batch and speed layers in the Lambda Architecture.

• In addition, queries only need to look in a single serving location instead of going against batch

and speed views.

Pros

• Kappa architecture can be used to develop data systems that are online learners and

therefore don’t need the batch layer.

• Re-processing is required only when the code changes.

• It can be deployed with fixed memory.

• It can be used for horizontally scalable systems.

• Fewer resources are required as the machine learning is being done on the real time basis.

Cons

• Absence of batch layer might result in errors during data processing or while updating the

database that requires having an exception manager to reprocess the data or reconciliation.

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