Redpanda vs Apache Kafka: C++ Thread-per-Core Architecture vs JVM Zero-Copy PageCache

Redpanda and Apache Kafka are two popular message brokers, each with their own strengths and weaknesses. Redpanda utilizes a thread-per-core architecture based on C++ and Seastar, while Kafka relies on the JVM and its zero-copy page cache.

Metrics such as p99 produce latency, end-to-end latency, and max sustained throughput per broker vary between the two systems. Redpanda tends to have lower latency (4.2 ms vs. 14.8 ms) and higher throughput (780 MB/s vs. 310 MB/s) compared to its Kafka counterpart (3.8.x). Additionally, Redpanda requires less RAM per broker in production (4 GB) and has no garbage collection (GC) pauses, whereas Kafka requires 6 GB heap + 6 GB page cache and experiences GC pauses ranging from 2–14 ms.

Cold-start to serving traffic and tiered storage costs also differ between the two. Redpanda has a faster cold-start (0.4 s) compared to Kafka (8–22 s), and both have similar tiered storage costs using native storage solutions. Wire protocols are compatible, with Redpanda offering a canonical implementation and Kafka providing a total ecosystem of additional features such as Kafka Streams, Connect sinks, and ksqlDB.

However, there are trade-offs to consider. Redpanda's thread-per-core architecture can lead to one slow core negatively impacting its partitions, while Kafka's thread-pool model helps redistribute work across idle threads. On hypervisors with bursty steal time, Redpanda's lead narrows, but it remains superior on bare metal. Additionally, the JVM in Kafka introduces managed runtime constraints, such as stop-the-world GC pauses and configuration limitations, which Redpanda avoids.

To summarize, choose Redpanda if you self-host, prioritize tail latency, and your stack doesn't require deep Kafka ecosystem features like Streams, Connect, or ksqlDB. Opt for Apache Kafka if you need the complete ecosystem, Apache-2.0 licensing, or prefer managed offerings like MSK or Confluent Cloud where operational costs dominate.