Disco MapReduce Alternatives
Disco MapReduce is described as 'Disco is an implementation of mapreduce for distributed computing. Disco supports parallel computations over large data sets, stored on an unreliable cluster of computers, as in the original framework created by Google' and is an app in the development category. There are six alternatives to Disco MapReduce for Linux, Mac, Windows, Online / Web-based and BSD. The best alternative is Apache Spark, which is both free and Open Source. Other great apps like Disco MapReduce are Apache Hadoop, Apache Flink, Amazon Kinesis and HPCC Systems.
Disco MapReduce alternatives are mainly Cloud Computing Services but may also be Web Analytics Services. Filter by these if you want a narrower list of alternatives or looking for a specific functionality of Disco MapReduce.
- Free • Open Source
- Mac
- Windows
- Linux
Apache Spark™ is a fast and general engine for large-scale data processing. Speed Run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk.
Spark has an advanced DAG execution engine that supports cyclic data flow and in-memory computing.
Apache Hadoop is a open source software framework that supports data-intensive distributed applications licensed under the Apache v2 license. It enables applications to work with thousands of computational independent computers and petabytes of data.
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- Free • Open Source
- Mac
- Windows
- Linux
- BSD
Flink’s core is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations over data streams.
No screenshots yetAmazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
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HPCC Systems offers an open source cluster computing platform used to solve Big Data problems. Its unique architecture and simple yet powerful data programming language (ECL) makes it a compelling solution to solve data intensive computing needs.
dispy is a Python framework for parallel execution of computations by distributing them across multiple processors on a single machine (SMP), among many machines in a cluster or grid.
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