Apache Kafka vs StreamNative

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.

StreamNative is a cloud data platform for capturing, transporting, transforming, governing, and serving business data in real time for applications, analytics, and agents. It provides native Kafka and Pulsar services powered by the Ursa engine, stream processing, schema registry support, and both listed delivery guarantees. Streams can be written directly to Iceberg and Delta tables in object storage. Universal Connect runs Kafka Connect and Pulsar IO connectors, including change-data-capture connectors, on one runtime. The platform supplies agents with governed context through open interfaces such as the StreamNative MCP Server. Deployment choices are Serverless, Dedicated, and BYOC in your cloud account, with AWS, Google Cloud, and Azure options. Serverless supports up to 100 MBps per namespace. Plans start at $73 a month for Serverless, $505 a month for Dedicated, and $365 a month for BYOC. Support is included in all plans, with 24/7 technical support available.