Resolve latency issues
This page shows you how to resolve latency issues with Firestore with MongoDB compatibility.
Latency
The following table describes possible causes of increased latency:
| Latency cause | Types of operations affected | Resolution |
|---|---|---|
| Sustained, increasing traffic. | read, write |
For rapid traffic increases, Firestore with MongoDB compatibility attempts to automatically scale to meet the increased demand. When Firestore with MongoDB compatibility scales, latency begins to decrease. Hot-spots (high read, write, and delete rates to a narrow document range) limit the ability of Firestore with MongoDB compatibility to scale. Review Avoid hot-spots and identify hot-spots in your application. |
| Contention, either from updating a single document too frequently or from transactions. | read, write |
Reduce the write rate to individual documents. Reduce the number of documents updated in a single write transaction. |
| Large reads that return many documents. | read | Use pagination to split large reads. |
| Too many recent deletes. | read This greatly affects operations that list collections in a database. |
If latency is caused by too many recent deletes, the issue should automatically resolve after some time. If the issue does not resolve, contact support. |
| Index fanout, especially for array fields and embedded document fields. | write | Review your indexing of array fields and embedded document fields. |
| Large writes. | write |
Try reducing the number of writes in each operation. For bulk data entry where you don't require atomicity, use parallelized individual writes. |