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The best Confluent Cloud alternatives
The rest of Best Stream Processing Software, in this site's order: each with what it costs, where it runs and its record score.
Apache Beam suits data and software developers building batch or streaming pipelines for supported execution back ends.
NiFi suits teams automating data flows across systems, including cybersecurity, observability, event stream, and generative AI pipelines.
Arroyo suits teams and developers building stateful data-stream pipelines with SQL, and those who need Rust user-defined functions.
AFL++ suits developers and security teams working with supported target types who need coverage-guided fuzzing.
Esper may suit developers building Java or .NET applications that process event streams.
Materialize suits teams building applications or AI agents that need continually updated SQL views from connected data sources.
Timeplus describes itself as designed for data engineers and platform teams processing streaming and historical data with SQL.
RisingWave may suit teams building streaming data pipelines with SQL and PostgreSQL-compatible tools.
Spark suits teams and developers working with large-scale analytics, batch jobs, or real-time streams.
Apache Storm is for developers and teams building self-hosted systems that process ongoing data streams.
Feldera suits teams that need to keep SQL views current as source data changes, including those working on real-time medallion architectures, fraud…
Hazelcast Platform suits teams building data-intensive, mission-critical AI workloads and real-time applications.
Pathway suits developers building data pipelines for analytics or AI over stored and live data.
Siddhi suits developers building event-driven applications, real-time analytics, data integration, notification, or rule-processing systems.
Flink suits teams building event-driven systems, stream or batch analytics, and data pipelines, especially those able to operate self-hosted cluster…
Samza suits developers building real-time data applications who can manage a self-hosted framework.
Kafka suits teams building event-streaming systems for data pipelines, integration, analytics, and related applications.
