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Storm - Distributed and fault-tolerant realtime computation


Storm is a distributed real time computation system. Storm makes it easy to reliably process unbounded streams of data, doing for real time processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more.

Apache Beam - Unified model for defining both batch and streaming data-parallel processing pipelines


Apache Beam is an open source, unified model for defining both batch and streaming data-parallel processing pipelines. Using one of the open source Beam SDKs, you build a program that defines the pipeline. The pipeline is then executed by one of Beam’s supported distributed processing back-ends, which include Apache Apex, Apache Flink, Apache Spark, and Google Cloud Dataflow.

Hazelcast Jet - Distributed data processing engine, built on top of Hazelcast


Hazelcast Jet is a distributed computing platform built for high-performance stream processing and fast batch processing. It embeds Hazelcast In Memory Data Grid (IMDG) to provide a lightweight package of a processor and a scalable in-memory storage. It supports distributed java.util.stream API support for Hazelcast data structures such as IMap and IList, Distributed implementations of java.util.{Queue, Set, List, Map} data structures highly optimized to be used for the processing

Time-series Framework


Core framework used to manage, process and respond to dynamic changes in fast moving streaming time-series data in real-time.