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The best Apache Heron alternatives
The rest of Best Streaming Analytics Software, in this site's order: each with what it costs, where it runs and its record score.
Confluent Cloud suits teams building real-time streaming, event-driven applications, analytics, or AI/ML workloads.
Apache Beam suits data and software developers building batch or streaming pipelines for supported execution back ends.
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.
Druid may suit teams building low-latency analytics for streaming or batch data, especially workloads involving high query concurrency or immediate…
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…
kdb+ suits organizations handling time-series workloads in areas such as trading, fraud detection, IoT monitoring, and other listed sectors.
Pathway suits developers building data pipelines for analytics or AI over stored and live data.
Ververica Platform is intended for enterprise production workloads, including critical applications that need stream processing and governance.
Pinot suits teams building real-time analytics or user-facing workloads that combine batch and streaming data.
It suits software teams building analytics and real-time production features on managed ClickHouse.
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.
