Aiven for Apache Flink
Fully managed Apache Flink service by Aiven.
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Discover top open-source software, updated regularly with real-world adoption signals.
Unified engine for high-throughput, low-latency stream and batch processing
Apache Flink delivers a streaming-first runtime that handles both real-time and batch workloads with exactly-once guarantees, flexible windowing, and native integration with Hadoop ecosystem components.
Apache Flink is a streaming-first framework that also supports batch workloads, providing a single runtime for diverse data processing needs. It offers high throughput while maintaining low event latency, and guarantees exactly-once fault tolerance through checkpointing and natural back‑pressure handling.
Flink runs on Unix‑like systems and integrates seamlessly with the Hadoop ecosystem—YARN, HDFS, HBase, and more. Developers can use fluent Java APIs (or Scala) and leverage built‑in libraries for graph processing, machine learning, and complex event processing. The project ships with externalized connectors for Kafka, JDBC, Elasticsearch, and many other sources, making it adaptable to modern data pipelines.
Ideal for engineers building real‑time analytics, ETL pipelines, or stateful stream applications that require precise time semantics and robust scalability.
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Primary APIs are available in Java and Scala; Python is supported via PyFlink.
Yes, Flink integrates with YARN, HDFS, HBase, and other Hadoop components.
Flink offers exactly-once processing guarantees through distributed snapshots.
Flink’s DataStream API supports event-time semantics and out-of-order processing.
Most connectors are externalized into separate Apache projects, such as Kafka, JDBC, and Elasticsearch.
Project at a glance
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