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Apache Kafka review
Rotem Fogel
Rotem Fogel
R&D Director at a tech vendor with 201-500 employees
Transforms data with efficient real-time analytics and has robust streaming...
Kafka requires fine-tuning to find the best architecture, number of nodes, and partitions for your use case. It’s a trial-and-error process with no one-size-fits-all solution. Issues may arise until it’s appropriately tuned. While it can scale out efficiently, scaling down is more challenging, making deleting data or reducing activity harder.

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