Hadoop Comes Under Which Technology

Hadoop is a technology that falls under the umbrella of big data and distributed computing. It is not a single technology but rather a framework that encompasses various components and tools for distributed storage and processing of large datasets. Hadoop is often associated with several related technologies and concepts, including:

1. Distributed Computing: Hadoop is designed to distribute data and processing tasks across a cluster of computers, allowing for parallel processing of large datasets. It is a foundational technology for distributed computing in the context of big data.

2. Big Data: Hadoop is a key technology for handling and analyzing big data, which refers to the massive volumes of data generated by organizations and applications. It provides the infrastructure to store, process, and analyze such data efficiently.

3. Distributed File Systems: Hadoop includes the Hadoop Distributed File System (HDFS), which is a distributed and fault-tolerant file system. It falls under the category of distributed file systems used for storing large datasets across multiple nodes.

4. Batch Processing: Hadoop’s MapReduce programming model is widely used for batch processing of data. It allows users to write programs to process and analyze data in parallel across a Hadoop cluster.

5. NoSQL and Big Data Ecosystem: Hadoop is part of the broader big data ecosystem, which includes various NoSQL databases (e.g., HBase, Cassandra), data processing frameworks (e.g., Apache Spark), and data storage solutions. These technologies work together to address different aspects of big data processing.

6. Open Source Software: Hadoop is an open-source technology developed and maintained by the Apache Software Foundation. It is freely available and has a large and active community of users and contributors.

7. Data Warehousing: While Hadoop itself is not a data warehousing technology, it is often used in conjunction with data warehousing solutions to handle large and diverse datasets for analytics and reporting.

8. Machine Learning: Hadoop can be used for distributed machine learning tasks, and it often works in conjunction with machine learning frameworks to train models on big data.