Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams.
Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale.
This is free and open source software.
Key Features
- A streaming-first runtime that supports both batch processing and data streaming programs.
- Elegant and fluent APIs in Java and Scala.
- A runtime that supports very high throughput and low event latency at the same time.
- Support for event time and out-of-order processing in the DataStream API, based on the Dataflow Model.
- Flexible windowing (time, count, sessions, custom triggers) across different time semantics (event time, processing time).
- Fault-tolerance with exactly-once processing guarantees.
- Natural back-pressure in streaming programs.
- Libraries for Graph processing (batch), Machine Learning (batch), and Complex Event Processing (streaming).
- Built-in support for iterative programs (BSP) in the DataSet (batch) API.
- Custom memory management for efficient and robust switching between in-memory and out-of-core data processing algorithms.
- Compatibility layers for Apache Hadoop MapReduce.
- Integration with YARN, HDFS, HBase, and other components of the Apache Hadoop ecosystem.
Website: flink.apache.org
Support: GitHub Code Repository
Developer: Apache Software Foundation
License: Apache License 2.0
Apache Flink is written in Java. Learn Java with our recommended free books and free tutorials.
Related Software
| Data Analysis Tools | |
|---|---|
| Hadoop | Distributed processing of large data sets across clusters of computers |
| Storm | Distributed and fault-tolerant realtime computation |
| Drill | Distributed system for interactive analysis of large-scale datasets |
| Flink | Framework and distributed processing engine |
| Spark | Unified analytics engine for large-scale data processing |
| Pentaho | Enterprise reporting, analysis, dashboard, data mining, workflow and more |
| HPCC Systems | Designed for the enterprise to resolve Big Data challenges |
| Daft | High-performance distributed data processing engine |
| Apache Beam | Unified programming model for batch and streaming data processing |
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