Apache Hadoop is a distributed data processing platform that enables the storage and processing of large datasets across multiple computers. It was originally developed by Apache Software Foundation in 2006 and has since become an integral part of many computing systems. It provides a framework that allows organizations to process large datasets with the help of commodity hardware. The software can be installed on any type of computer, including desktops, laptops, and servers.
Hadoop uses the MapReduce programming model to process data in parallel. This provides an efficient way to process large amounts of information quickly by splitting the workload among different computers. Additionally, it’s designed to be fault tolerant which means it will continue working even if one or more nodes fail. This ensures that data is not lost or corrupted during processing.
The software also supports many open source projects such as Hive, Pig, Impala, and HBase which allow for more advanced querying and analysis capabilities on top of the core Hadoop platform. Additionally, it’s compatible with popular scripting languages like Python and R which can be used to analyse data stored in Hadoop clusters.
Overall, Apache Hadoop provides a powerful framework for distributed data storage and analysis that can easily scale up or down depending on demand. It’s also open source which makes it accessible to everyone regardless of their budget or technical knowledge level.