jdbc vs hibernate

In this section, you will learn why hibernate is better option than using JDBC.

jdbc vs hibernate

jdbc vs hibernate

In this section, you will learn why hibernate is better option than using JDBC.

JDBC HIBERNATE
Need manual mapping for an object model's data representation to a relational data model. Hibernate has its own efficient ORM feature which take care of the mapping itself using XML files.
You need to write query for database connection explicitly.  Hibernate automatically connect to the database by using the XML configuration file. 
JDBC supports SQL only. Developers need to explicitly write the whole query and choose according to your need. Hibernate supports HQL(Hibernate query language) and native SQL.
In JDBC, mapping between two tables needs to write lots of codes and query. And if there is change in database or table, you need to change the code and the query as well. In Hibernate, the mapping between two tables done through the XML or annotation and if there is a change in database or in any table, you need to change the XML file or annotated  model  class.
In JDBC, caching is maintained through code written explicitly. In Hibernate, cache is fixed to application work space. The results of the query is move to this cache, so that after some time when user wants to fetch the same record, the cached records can be used. It will also save time.
In JDBC, no check is present which store the updated data information by any user which checks every time data updating occurs. If developer want this type of check, he need to code it himself. In Hibernate, version type field is present, which is enabled by the developer. Each time when database is updated in form of java class object, version type field is updated. So if the same row is retrieved by two peoples and one of them tried to update it, version is automatically updated for this row by Hibernate. When other user tries to update the same row, it will not allow them to update this row because the user contains the data of the row before last updation.