jstorm - Enterprise Stream Process Engine

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Alibaba JStorm is an enterprise fast and stable streaming process engine. It runs program up to 4x faster than Apache Storm. It is easy to switch from record mode to mini-batch mode. It is not only a streaming process engine. It means one solution for real time requirement, whole realtime ecosystem.

stream-processing batch-processing real-time data-processing distributed

Fluo - Make incremental updates to large data sets stored in Apache Accumulo

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Apache Fluo (incubating) is an open source implementation of Percolator (which populates Google's search index) for Apache Accumulo. Fluo makes it possible to update the results of a large-scale computation, index, or analytic as new data is discovered. When combining new data with existing data, Fluo offers reduced latency when compared to batch processing frameworks (e.g Spark, MapReduce).

percolator incremental-updates batch-processing big-data

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

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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.

data-processing data-streaming batch-processing stream-processing distributed big-data

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

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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

data-grid data-processing data-streaming in-memory batch-processing stream-processing

batch-shipyard - Execute batch and HPC Dockerized workloads on Azure Batch with shared file system provisioning and linking support

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Additionally, Batch Shipyard provides the ability to provision and manage entire standalone remote file systems (storage clusters) in Azure, independent of any integrated Azure Batch functionality.Batch Shipyard is now integrated directly into Azure Cloud Shell and you can execute any Batch Shipyard workload using your web browser or the Microsoft Azure Android and iOS app.

azure-batch docker hpc mpi gpu infiniband rdma azure nvidia-docker batch-processing nfs glusterfs smb azure-functions