# MongoDB Locking Explained: Summary of Concurrency and Locking Strategies

When working with high-concurrency workloads in MongoDB, understanding how locking and concurrency control work is essential to maintain performance and data integrity. Here’s a quick overview of the core ideas:

### Key Highlights:

* **Document-Level Locking**: With the WiredTiger engine, MongoDB supports fine-grained locks at the document level.
    
* **Lock Types**: Internally uses Shared (S), Exclusive (X), Intent Shared (IS), and Intent Exclusive (IX) for coordination.
    
* **Optimistic Locking**: Uses a version field to prevent overwrites in high-read environments.
    
* **Pessimistic Locking**: Simulated via a `lock` field to prevent concurrent access during critical updates.
    
* **Deadlock Prevention**: Implement retry logic, consistent update order, and use `$maxTimeMS` to avoid transaction stalls.
    
* **Monitoring Tools**: Use `serverStatus().locks` and `currentOp({ waitingForLock: true })` to track lock contention.
    

### Use Cases Covered:

* Real-world optimistic & pessimistic lock patterns in MongoDB
    
* Deadlock detection and prevention strategies
    
* Lock optimization techniques and when to use which approach
    

| Scenario | Best Strategy |
| --- | --- |
| High Reads, Low Conflict | Optimistic Locking |
| High Write Contention | Pessimistic Locking |
| Multi-doc Transactions | Retry on Deadlocks |

More details are posted [here at another post](https://databasedeveloper.dev/mastering-mongodb-locking-concurrency-and-performance-optimization-a-deep-dive)