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 Petabytes||In 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 Hive||Record level updates, insertions,|
Deletes and transactions are possible.
|Hive is very easily scalable at low cost||RDBMS 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/reduce||Distributed 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.