source – Database-based timestamps incur an overhead because Hibernate needs to query the database each time to determine the incremental next value.generated – indicates that the timestamp property value is generated by the database.The default value, undefined, indicates that the identifier property value should be used. This distinguishes it from detached instances that were saved or loaded in a previous session. unsaved-value – indicates that an instance is newly instantiated and thus unsaved.access – Hibernate’s strategy for accessing the property value.type – the type of the version number.name – the name of a JavaBeans style property of Java type Date or Timestamp of the persistent class.

column – the name of the column holding the timestamp.The timestamp can also be generated by the database instead of Hibernate, if you use the annotation. The default behavior is to use the database, and is also used if you don’t specify the annotation at all. Hibernate can retrieve the timestamp value from the database or the JVM, by reading the value you specify for the annotation. The version number mechanism for optimistic locking is provided through a annotation. Hibernate provides two different mechanisms for storing versioning information, a dedicated version number and a timestamp. This approach guarantees some isolation, but scales well and works particularly well in read-frequently write-sometimes situations. When your application uses long transactions or conversations that span several database transactions, you can store versioning data, so that if the same entity is updated by two transactions, to commit the modification changed by last transaction is informed of the conflict, and does not override the other transaction’s work. If conflicting modification is revealed, then the committing transaction rolls back.Before committing, each transaction verifies that no other transaction has modified its data.Transactions can proceed without locking the data resources that they affect.Multiple transactions can complete without affecting each other.There are mainly two types of locking strategy available – optimistic and pessimistic Optimistic

Locking refers to a mechanism taken for granted in a relational database to prevent any modification to the data between the time the data are read and the time the data are used.

Readwrite lock in spring