Apache Hadoop is described as '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' and is an app in the development category. There are more than 10 alternatives to Apache Hadoop for a variety of platforms, including Linux, Mac, Windows, Web-based and SaaS apps. The best Apache Hadoop alternative is Apache Spark, which is both free and Open Source. Other great apps like Apache Hadoop are Amazon Kinesis, ILUM, Gigasheet and Apache Flink.
Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters.
Apache Spark is the most popular Self-Hosted alternative to Apache Hadoop.
Apache Spark is the most popular Open Source & free alternative to Apache Hadoop.
Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
Amazon Kinesis is the most popular SaaS alternative to Apache Hadoop.
Amazon Kinesis is the most popular commercial alternative to Apache Hadoop.
Gigasheet is the most popular Web-based alternative to Apache Hadoop.
Flink’s core is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations over data streams.
Apache Flink is the most popular Windows, Mac & Linux alternative to Apache Hadoop.
Disco is a lightweight, open-source framework for distributed computing based on the MapReduce paradigm and written in Python.
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. dispy is well suited for data parallell (SIMD) paradigm where a computation is evaluated with...
Upsolver is an In-Memory Data Preparation Platform. It removes the complexity from Big Data and Real-Time projects and shortens their implementation time from weeks/months to several hours, literally.
Object storage has been nothing short of revolutionary. S3 broke ground in 2006 with simple storage operations on named objects – and 18 years later, S3 Express One Zone even allows appends. But ultimately, object storage is all about blobs and byte ranges.
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