Apache Kafka's scalability is primarily due to its distributed architecture, which allows it to handle high-throughput and provides low-latency, fault-tolerant, and scalable data processing. Key factors contributing to its scalability include its ability to partition topics across multiple brokers, replicate data for fault tolerance, and handle large volumes of data through efficient data serialization and deserialization. Additionally, Kafka's design allows for horizontal scaling by simply adding more brokers to the cluster as needed.
Key Takeaways
Distributed architecture
Data partitioning and replication
Horizontal scaling
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