A collection of open-source tools and frameworks for distributed storage and processing of big data across clusters of computers.
Hadoop is built on HDFS (Hadoop Distributed File System) for storage and YARN for resource management, enabling scalable and fault-tolerant data processing.
Core components include MapReduce (batch processing), Hive (SQL-like queries), Pig (data flow scripting), and HBase (NoSQL database).
Ecosystem tools like Spark (in-memory processing), Kafka (streaming), and Flink (real-time analytics) extend Hadoop's capabilities beyond batch processing.
Hadoop enables cost-effective storage and processing of petabytes of data across commodity hardware clusters.
Used in big data analytics, machine learning pipelines, log processing, and ETL workflows across industries like finance, healthcare, and e-commerce.