What are the main features of Hadoop?

Here are the main features of Hadoop: 1. **Scalability**: - Easily scales out by adding more nodes to the cluster without downtime. 2. **Fault Tolerance**: - Data is replicated across multiple nodes, ensuring high availability and reliability even in case of hardware failures. 3. **Distributed Storage**: - Uses Hadoop Distributed File System (HDFS) to store large datasets across multiple machines in a distributed manner. 4. **Cost-Effective**: - Built to run on commodity hardware, reducing costs for storage and processing. 5. **High Throughput**: - Optimized for high data processing throughput, making it suitable for handling large volumes of data. 6. **Data Locality**: - Moves computation closer to where data is stored, reducing network congestion and improving processing speed. 7. **Support for Various Data Types**: - Can process structured, semi-structured, and unstructured data from diverse sources. 8. **Extensive Ecosystem**: - Integrates with various tools and frameworks (e.g., Apache Hive, Apache Pig, Apache Spark) for data processing, querying, and analytics. 9. **Batch Processing**: - Primarily designed for batch processing of large datasets, although it can also support real-time processing with additional tools. 10. **Open Source**: - Being open-source allows for community contributions, flexibility, and customization. ### Summary: Hadoop’s scalability, fault tolerance, distributed storage, and ability to handle various data types make it a powerful framework for big data storage and processing. read less