distributed stream processing
Apache Flink is a JVM-based distributed stream processing framework with batch-processing capabilities, exactly-once fault tolerance, and event-time semantics.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Choose when you want embedded stream processing co-located with an in-memory data grid instead of a separate Flink cluster.
Hazelcast is a unified real-time data platform combining stream processing with a fast data store, allowing customers to act instantly on data-in-motion for real-time insights.
Choose for Rust-based edge-to-cloud event streaming with built-in messaging rather than a JVM stream processing cluster.
🦀 event stream processing for developers to collect and transform data in motion to power responsive data intensive applications.
Choose for Python-native stream processing and LLM pipelines, accepting a smaller ecosystem than Flink.
Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
Choose for a SQL streaming database with Postgres compatibility, avoiding Flink's separate compute cluster.
Event streaming platform for agentic AI. Continuously ingest, transform, and serve event streams in real time, at scale.
Choose for Postgres-compatible SQL materialized views over streams, trading Flink's general computation for a database interface.
The live data layer for apps and AI agents. Create up-to-the-second views into your business, just using SQL
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Choose for lightweight Python stream processing on Kafka if you don't need Flink's scale, but it is stale and less mature.
Python Stream Processing
Choose only for legacy JVM spout/bolt pipelines where Flink's newer API is not needed.
Distributed and fault-tolerant realtime computation: stream processing, continuous computation, distributed RPC, and more
These projects were analysed and named flink among their alternatives. The relationship is not symmetric — how flink rates them is a separate judgement, made when flink is analysed in its own right.
calls flink “choose when you need a standalone stream-processing engine and will provide external storage instead of using Hazelcast's built-in store.”
Hazelcast is a unified real-time data platform combining stream processing with a fast data store, allowing customers to act instantly on data-in-motion for real-time insights.