What distinguishes HBase from Hadoop/HDFS?

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Hadoop is a distributed computing framework that consists of two major components: HDFS (Hadoop Distributed File System) and MapReduce. HDFS is a distributed file system that provides reliable and efficient storage for large datasets, while MapReduce is a programming model and software framework for large-scale data processing.

HBase, on the other hand, is a NoSQL database that is built on top of HDFS. It provides random, real-time read and write access to the data stored in HDFS, whereas HDFS is designed for batch processing of large data sets. HBase also supports column-family based data storage, which enables efficient storage and retrieval of complex data structures.

So, the main difference between HBase and Hadoop/HDFS is that HBase provides real-time, random access to data stored in HDFS, while HDFS is designed for batch processing of large datasets. Additionally, HBase provides support for column-family based data storage, which is not available in HDFS.