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HDFS vs. HBase : All you need to know

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The sudden increase in the volume of data from the order of gigabytes to zettabytes has created the need for a more organized file system for storage and processing of data. The demand stemming from the data market has brought Hadoop in the limelight making it one of biggest players in the industry. Hadoop Distributed File System (HDFS), the commonly known file system of Hadoop and HBase (Hadoop’s database) are the most topical and advanced data storage and management systems available in the market.

What are HDFS and HBase?

HDFS is fault-tolerant by design and supports rapid data transfer between nodes even during system failures. HBase is a non-relational and open source Not-Only-SQL database that runs on top of Hadoop. HBase comes under CP type of CAP (Consistency, Availability, and Partition Tolerance) theorem.

HDFS is most suitable for performing batch analytics. However, one of its biggest drawbacks is its inability to perform real-time analysis, the trending requirement of the IT industry. HBase, on the other hand, can handle large data sets and is not appropriate for batch analytics. Instead, it is used to write/read data from Hadoop in real-time.

Both HDFS and HBase are capable of processing structured, semi-structured as well as unstructured data. …

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