Apache Kafka vs Timely Dataflow

Apache Kafka is an open-source distributed event-streaming platform for data pipelines, streaming analytics, data integration, and mission-critical applications. Applications can publish and subscribe to event streams, retain them durably, and process them either in real time or later. Kafka supports durable, fault-tolerant replication across availability zones, data centers, or geographic regions. Kafka Streams provides stateful operations, aggregations, windowing, joins, event-time processing, and exactly-once processing. Kafka Connect links hundreds of event sources and sinks, including Postgres, JMS, Elasticsearch, and AWS S3. Deployments can use bare metal, virtual machines, or containers, on premises or in the cloud, with self-managed or vendor-managed options. The project describes network-limited throughput, latency as low as 2 ms, and clusters of up to 1,000 brokers. Kafka is self-hosted, free, and open source under Apache License 2.0. A local quickstart requires Java 17 or later.

Timely Dataflow has no write-up on Specifiction yet; its figures are above.