Apache Hadoop, an ecosystem of open source components and software is reliable, scalable, distributed for computing. It offers a framework for distributed processing and storage of big data using simple programming models. Apache Hadoop is designed to scale up from a single server to hundreds and thousands of machines. With each machine offering a local computation and storage. The specialty of this software is that it doesn’t rely on hardware; the library is designed to detect and handle failures at the application layer. This makes it highly available by avoiding any hardware failures on top of a cluster of computers.
The Java-based programming framework allows users to run applications on systems with thousands of commodity nodes which mean it can handle thousands of terabytes of data. It allows rapid data transfer because of its distributed file system which in turn allows the system to continue operating in case of node failure. Some of the benefits of using Apache Hadoop is that it is:
Scalable: The cluster enables Hadoop to manage, store, process and analyze data at petabyte scale.
Reliable: While large computing clusters are prone to failure, Hadoop is fundamentally resilient. When a node fails, processing and data are re-directed to the remaining nodes making it reliable.
Flexible: Creating structured schemes for storing data isn’t required here. Data here can be stored in any formats including semi-structured or unstructured formats.
Cost effective: Hadoop is available as open source software and runs on low-cost commodity hardware.
Companies Using Apache Hadoop, Market Share & Customers List
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Companies Currently Using Apache Hadoop (Sample Data)
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