HBASE

What is HBase used as?

HBase is a column-oriented non-relational database management system that runs on top of Hadoop Distributed File System (HDFS). HBase provides a fault-tolerant way of storing sparse data sets, which are common in many big data use cases. ... HBase does support writing applications in Apache Avro, REST and Thrift.

Is HBase a NoSQL database?

Apache HBase is a NoSQL key/value store which runs on top of HDFS. ... Unlike Hive, HBase operations run in real-time on its database rather than MapReduce jobs. HBase is partitioned to tables, and tables are further split into column families

Why HBase is faster than Hive?

Unlike Hive, HBase operations run in real-time on its database rather than MapReduce jobs. Apache Hive is a data warehouse system that's built on top of Hadoop. ... Apache Hive provides SQL features to Spark/Hadoop data. HBase can store or process Hadoop data with near real-time read/write needs

When you should use HBase?

In summary, consider HBase when you're loading data by key, searching data by key (or range), serving data by key, querying data by key or when storing data by row that doesn't conform well to a schema.

Apache HBase is used to have random, real-time read/write access to Big Data.

It hosts very large tables on top of clusters of commodity hardware.

Apache HBase is a non-relational database modeled after Google's Bigtable. Bigtable acts up on Google File System, likewise Apache HBase works on top of Hadoop and HDFS.

What is difference between  HDFS and HBase?

The following points need to be emphasized on:

HDFS vs HBase

HDFS is a Java-based file system utilized for storing large data sets. HBase is a Java based Not Only SQL database

HDFS has a rigid architecture that does not allow changes. It doesn’t facilitate dynamic storage. HBase allows for dynamic changes and can be utilized for standalone applications.

HDFS is ideally suited for write-once and read-many times use cases HBase is ideally suited for random write and read of data that is stored in HDFS.