Displaying 1 to 20 from 35 results

CloverETL - Rapid Data Integration

  •    Java

Java based data integration framework can be used to transform/map/manipulate data in various formats (CSV,FIXLEN,XML,XBASE,COBOL,LOTUS, etc.); can be used standalone or embedded(as a library). Connects to RDBMS/JMS/SOAP/LDAP/S3/HTTP/FTP/ZIP/TAR.

Vespa - Yahoo's big data serving engine

  •    Java

Vespa is an engine for low-latency computation over large data sets. It stores and indexes your data such that queries, selection and processing over the data can be performed at serving time. Vespa is serving platform for Yahoo.com, Yahoo News, Yahoo Sports, Yahoo Finance, Yahoo Gemini, Flickr.

jstorm - Enterprise Stream Process Engine

  •    Java

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.




DataflowJavaSDK - Google Cloud Dataflow provides a simple, powerful model for building both batch and streaming parallel data processing pipelines

  •    Java

Google Cloud Dataflow SDK for Java is a distribution of Apache Beam designed to simplify usage of Apache Beam on Google Cloud Dataflow service. This artifact includes the parent POM for other Dataflow SDK artifacts.

Hub - Fastest dataset optimization and management for machine and deep learning

  •    Python

Note: the translations of this document may not be up-to-date. For the latest version, please check the README in English. Software 2.0 needs Data 2.0, and Hub delivers it. Most of the time Data Scientists/ML researchers work on data management and preprocessing instead of training models. With Hub, we are fixing this. We store your (even petabyte-scale) datasets as single numpy-like array on the cloud, so you can seamlessly access and work with it from any machine. Hub makes any data type (images, text files, audio, or video) stored in cloud usable as fast as if it were stored on premise. With same dataset view, your team can always be in sync.


Apache Flink - Platform for Scalable Batch and Stream Data Processing

  •    Java

Apache Flink is an open source platform for scalable batch and stream data processing. Flink’s core is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations over data streams.

Apache REEF - a stdlib for Big Data

  •    Java

Apache REEF (Retainable Evaluator Execution Framework) is a library for developing portable applications for cluster resource managers such as Apache Hadoop YARN or Apache Mesos. For example, Microsoft Azure Stream Analytics is built on REEF and Hadoop.

Apache Storm - Distributed and fault-tolerant realtime computation

  •    Java

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 Tez - A Framework for YARN-based, Data Processing Applications In Hadoop

  •    Java

Apache Tez is an extensible framework for building high performance batch and interactive data processing applications, coordinated by YARN in Apache Hadoop. Tez improves the MapReduce paradigm by dramatically improving its speed, while maintaining MapReduce’s ability to scale to petabytes of data. Important Hadoop ecosystem projects like Apache Hive and Apache Pig use Apache Tez, as do a growing number of third party data access applications developed for the broader Hadoop ecosystem.

Hazelcast Jet - A general purpose distributed data processing engine, built on top of Hazelcast.

  •    Java

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, simple-to-deploy package that includes scalable in-memory storage. Hazelcast Jet performs parallel execution to enable data-intensive applications to operate in near real-time.

Kapacitor - Open source framework for processing, monitoring, and alerting on time series data

  •    Go

Kapacitor is a open source framework for processing, monitoring, and alerting on time series data. Kapacitor imports (stream or batch) time series data, and then transform, analyze, and act on the data. It uses Telegraf to collect system metrics on your local machine and store them in InfluxDB.

Broadway - Concurrent and multi-stage data ingestion and data processing with Elixir

  •    Elixir

Build concurrent and multi-stage data ingestion and data processing pipelines with Elixir. It allows developers to consume data efficiently from different sources, known as producers, such as Amazon SQS, Apache Kafka, Google Cloud PubSub, RabbitMQ, and others. Broadway takes the burden of defining concurrent GenStage topologies and provide a simple configuration API that automatically defines concurrent producers, concurrent processing, batch handling, and more, leading to both time and cost efficient ingestion and processing of data.

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

  •    Java

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

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

  •    Java

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.

Teiid - Data virtualization system that allows applications to use data from multiple, heterogeneous data stores.

  •    Java

Teiid is a data virtualization system that allows applications to use data from multiple, heterogenous data stores. Teiid is comprised of tools, components and services for creating and executing bi-directional data access services.

NIPO Data Processing Component Framework

  •    

NIPO is a general purpose component framework for data processing applications (that follow the IPO-principle). Its plugin-based architecture makes it scalable, flexible and enables a broad range of usage scenarios.

NPipeline

  •    DotNet

NPipeline is a .NET port of the Apache Commons Pipeline components. It is a lightweight set of utilities that make it simple to implement parallelized data processing systems.






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