5 HBase Vs. RDBMS Top Functional Differences

HBASE in the Big data context has a lot of benefits over RDBMS. Clear difference makes you feel great why you need HBASE in Hadoop or Bigdata platform. Let us check one by one quickly.


HBASE and RDBMS have functional differences. I have explained how the HBASE is preferable in the Hadoop framework.

HBASE Vs. RDBMS


  • HBase handles a large amount of data that is store in a distributed manner in the column-oriented format while RDBMS is systematic storage of a database that cannot support a random manner for accessing the database.

  • RDBMS strictly follow Codd's 12 rules with fixed schemas and row-oriented manner of database and also follow ACID properties, while HBase follows BASE properties and implement complex queries.

  • Secondary indexes, complex inner and outer joins, count, sum, sort, group, and data of page and table can easily be accessible by RDBMS.

  • From small to medium storage application there is the use of RDBMS that provide the solution with MySQL and PostgreSQL whose size increase with concurrency and performance. Codd's rules always need to keep in mind while extending the size of the database in the use of data processing.

  • RDBMS focus and emphasizes on consistency, referential integrity, abstraction from the physical layer, and complex queries through SQL language.


Takeaways

  1. There is no single-point failure in HBASE. You always have backup data.
  2. The server regions have the flexibility to share or rebalance the load among the servers.
  3. Automatic partition helps to distribute its workload among servers. It happens with its in-built feature of HBASE.
  4. The cost involved for the maintenance of HBASE is comparatively low.


Keep Reading

  1. Hbase: The Definitive Guide- Random Access to Your Planet-Size Data
  2. Hbase Database for beginners: Learn how to Create, Use and Handle an Hbase Database from Scratch

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