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Berkeley DB Reference Guide:
  Berkeley DB Transactional Data Store Applications

### Atomicity

The second reason listed for using transactions was atomicity. Atomicity means that multiple operations can be grouped into a single logical entity, that is, other threads of control accessing the database will either see all of the changes or none of the changes. Atomicity is important for applications wanting to update two related databases (for example, a primary database and secondary index) in a single logical action. Or, for an application wanting to update multiple records in one database in a single logical action.

Any number of operations on any number of databases can be included in a single transaction to ensure the atomicity of the operations. There is, however, a trade-off between the number of operations included in a single transaction and both throughput and the possibility of deadlock. The reason for this is because transactions acquire locks throughout their lifetime and do not release the locks until commit or abort time. So, the more operations included in a transaction, the more likely it is that a transaction will block other operations and that deadlock will occur. However, each transaction commit requires a synchronous disk I/O, so grouping multiple operations into a transaction can increase overall throughput. (There is one exception to this: the DB_TXN_WRITE_NOSYNC and DB_TXN_NOSYNC flags cause transactions to exhibit the ACI (atomicity, consistency and isolation) properties, but not D (durability); avoiding the write and/or synchronous disk I/O on transaction commit greatly increases transaction throughput for some applications.)

When applications do create complex transactions, they often avoid having more than one complex transaction at a time because simple operations like a single DB->put are unlikely to deadlock with each other or the complex transaction; while multiple complex transactions are likely to deadlock with each other because they will both acquire many locks over their lifetime. Alternatively, complex transactions can be broken up into smaller sets of operations, and each of those sets may be encapsulated in a nested transaction. Because nested transactions may be individually aborted and retried without causing the entire transaction to be aborted, this allows complex transactions to proceed even in the face of heavy contention, repeatedly trying the suboperations until they succeed.

It is also helpful to order operations within a transaction; that is, access the databases and items within the databases in the same order, to the extent possible, in all transactions. Accessing databases and items in different orders greatly increases the likelihood of operations being blocked and failing due to deadlocks.

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