Question: How can I improve MongoDB writes per second?

Answer

Improving MongoDB's write throughput – the number of write operations performed per second – involves several strategies focusing on hardware, database schema design, and MongoDB configuration. Here are some methods to consider:

1. Use WiredTiger Storage Engine

Ensure you're using the WiredTiger storage engine, which is the default for MongoDB versions 3.2 and above. It offers better concurrency and compression, directly impacting write performance.

// To check your current storage engine, run the following command in the mongo shell: db.serverStatus().storageEngine

2. Sharding

Distribute your data across multiple machines using sharding. This approach splits data into smaller, more manageable parts, allowing for horizontal scaling and distributing write load.

3. RAID Configuration

Use RAID 10 (mirroring and striping) for your disk setup. It offers a balance of speed and redundancy, improving write performance while ensuring data safety.

4. Write Concerns

Adjust your write concern levels based on your application's consistency requirements. Less strict write concerns ({w: 0} or {w: 1}) can increase write speed but at the cost of data durability and consistency.

db.collection.insertOne( { item: "card", qty: 15 }, { writeConcern: { w: 1 } } )

5. Indexing

Ensure that your indexes support your write patterns. Inefficient indexing can slow down writes due to the overhead of updating indexes. However, be cautious not to over-index as each additional index requires updates on write operations.

6. Hardware Improvements

  • RAM: More RAM allows MongoDB to keep larger working sets in memory, reducing disk I/O.
  • SSD: Solid State Drives significantly improve read/write speeds compared to traditional HDDs.

7. Connection Pooling

Maintain a pool of database connections to avoid the overhead of establishing connections for every write operation. Most MongoDB drivers handle connection pooling automatically.

8. Bulk Operations

Use bulk inserts or updates when possible. Grouping multiple write operations in a single command reduces overhead and improves throughput.

db.collection.bulkWrite([ { insertOne: { document: { a: 1 } } }, { updateOne: { filter: {a: 2}, update: {$set: {a: 2}}, upsert:true } }, { deleteOne: { filter: {c: 1} } } ])

9. Avoid Jumbo Chunks in Sharded Clusters

In sharded setups, ensure chunks are split and balanced properly. Jumbo chunks can prevent efficient distribution of data and operations across shards.

Implementing these strategies can significantly improve your MongoDB write performance. However, always monitor and test changes in a staging environment before applying them to production to understand their impact.

Was this content helpful?

Start building today

Dragonfly is fully compatible with the Redis ecosystem and requires no code changes to implement.