Software Alternatives & Reviews


Open-source software for reliable, scalable, distributed computing

Hadoop Alternatives

The best Hadoop alternatives based on verified products, community votes, reviews and other factors.
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  1. Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

  2. The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.

  3. MongoDB (from "humongous") is a scalable, high-performance, open source NoSQL database.


  4. PostgreSQL is a powerful, open source object-relational database system.

  5. Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

  6. Apache Storm is a free and open source distributed realtime computation system.

  7. Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

  8. The world's most popular open source database

  9. A fully managed data warehouse for large-scale data analytics.

  10. Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

  11. Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

  12. Hadoop-Related

  13. Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.

Hadoop Reviews

External sources with reviews and comparisons of Hadoop

16 Top Big Data Analytics Tools You Should Know About
Hadoop is an Apache open-source framework. Written in Java, Hadoop is an ecosystem of components that are primarily used to store, process, and analyze big data. The USP of Hadoop is it enables multiple types of analytic workloads to run on the same data, at the same time, and on a massive scale on industry-standard hardware.
5 Best-Performing Tools that Build Real-Time Data Pipeline
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than relying on hardware to...
Read all Hadoop reviews →

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Author: | Publisher: SaaSHub
Categories: Databases, Big Data, NoSQL Databases