The Howdy Glossary

Apache Hadoop is an open-source framework designed for distributed storage and processing of vast data sets on computer clusters. Key components include the Hadoop Distributed File System (HDFS) for data storage and MapReduce for parallel job processing across clusters. Additional components like YARN manage resources, enabling scalability and multi-tenancy, while seamlessly integrating with other Apache projects such as Hive, Pig, HBase, and Spark for diverse big data needs. This extensibility allows users to create customized solutions without reliance on proprietary tools or hardware vendors.

Initially created by Doug Cutting and Mike Cafarella in 2005, inspired by Google's GFS and MapReduce whitepapers, Hadoop was developed to provide a scalable solution for large data set processing. It quickly became an Apache Software Foundation project due to its growing popularity and contributions from a global community of developers. The framework's evolution has incorporated additional tools that cement its position as a versatile platform in the big data ecosystem.

Hadoop’s robust architecture features fault-tolerant HDFS for reliable data storage and MapReduce for efficient parallel processing across clusters. Its extensibility through components like YARN enables resource management while integration with various Apache projects provides tailored solutions independent of proprietary software or hardware constraints. Despite competition from frameworks like Apache Spark, known for in-memory processing speed; Apache Flink's stream processing efficiency; AWS's managed big data services; and Cloudera’s enterprise-focused distribution—Hadoop remains favored due to its flexibility, scalability, community support, and comprehensive ecosystem integrations.