Difference between Hive and RDBMS

Let us discuss Difference between Hive and RDBMS



Hive enforces schema on read

i.e schema does’t not verify loading data.

RDBMS enforces schema on write

i.e schema verify loading data,else rejected.

Hive is based on the notion of Write once, Read many times.RDBMS is designed for Read and Write many times.
Hive data size is PetabytesIn RDBMS, maximum data size is Terabytes
Hive doesn’t support OLTP (Online Transaction Processing) but it support OLAP (Online Analytical Processing)RDBMS supports only OLTP.
Hive is suited for static data analysis(non real time data) example text file.RDBMS is best suited for dynamic data analysis(real time data) example data from the sensors and web feeds.
Record level updates is not possible in HiveRecord level updates, insertions,

Deletes and transactions are possible.

Hive is very easily scalable at low costRDBMS is not scalable to low cost,because it provide solution to the customers.
Hive resembles a traditional DB by supporting SQL but it is not a database.It is a database.
No support for indexes because data is always scanned.

Supports  indexes, it is very important for Performance.

Focus on only analytics.Focus on analytics or online(device connected to network).


Distributed processing  done via map/reduceDistributed processing varies by vendor(company or person).
Scales up to hundred of nodes.Scales to beyond 20 nodes.

From the above topic “Difference between Hive and RDBMS” we can conclude that both are used in bigdata for OLTP and OLAP.