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Difference Between HDFS and HBase

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  • Last Updated : 17 May, 2020
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HDFS: Hadoop Distributed File System is a distributed file system designed to store and run on multiple machines that are connected to each other as nodes and provide data reliability. It consists of clusters, each of which is accessed through a single NameNode software tool installed on a separate machine to monitor and manage the that cluster’s file system and user access mechanism.

HBase: HBase is a top-level Apache project written in java which fulfills the need to read and write data in real-time. It provides a simple interface to the distributed data. It can be accessed by Apache Hive, Apache Pig, MapReduce, and store information in HDFS.


Below is a table of differences between HDFS and HBase:

HDFS is a java based file distribution system Hbase is hadoop database that runs on top of HDFS
HDFS is highly fault-tolerant and cost-effective HBase is partially tolerant and highly consistent
HDFS Provides only sequential read/write operation Random access is possible due to hash table
HDFS is based on write once read many times HBase supports random read and writeoperation into filesystem
HDFS has a rigid architecture HBase support dynamic changes
HDFS is prefereable for offline batch processing HBase is preferable for real time processing
HDFS provides high latency for access operations. HBase provides low latency access to small amount of data
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