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- Atomicity and Transactions
Atomicity and Transactions¶
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Atomicity¶
In MongoDB, a write operation is atomic on the level of a single document, even if the operation modifies multiple embedded documents within a single document.
Multi-Document Transactions¶
When a single write operation (e.g.
db.collection.updateMany()) modifies multiple documents,
the modification of each document is atomic, but the operation as a
whole is not atomic.
When performing multi-document write operations, whether through a single write operation or multiple write operations, other operations may interleave.
For situations that require atomicity of reads and writes to multiple documents (in a single or multiple collections), MongoDB supports multi-document transactions:
- In version 4.0, MongoDB supports multi-document transactions on replica sets.
- In version 4.2, MongoDB introduces distributed transactions, which adds support for multi-document transactions on sharded clusters and incorporates the existing support for multi-document transactions on replica sets.
For details regarding transactions in MongoDB, see the Transactions page.
Important
In most cases, multi-document transaction incurs a greater performance cost over single document writes, and the availability of multi-document transactions should not be a replacement for effective schema design. For many scenarios, the denormalized data model (embedded documents and arrays) will continue to be optimal for your data and use cases. That is, for many scenarios, modeling your data appropriately will minimize the need for multi-document transactions.
For additional transactions usage considerations (such as runtime limit and oplog size limit), see also Production Considerations.
Concurrency Control¶
Concurrency control allows multiple applications to run concurrently without causing data inconsistency or conflicts.
One approach is to create a unique index on a field that can only have unique values. This prevents insertions or updates from creating duplicate data. Create a unique index on multiple fields to force uniqueness on that combination of field values. For examples of use cases, see update() and Unique Index and findAndModify() and Unique Index.
Another approach is to specify the expected current value of a field in the query predicate for the write operations.