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This page shows you how to resolve latency issues with Cloud Firestore.

## 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, Cloud Firestore attempts to automatically scale to meet the increased demand. When Cloud Firestore scales, latency begins to decrease. Hot-spots (high read, write, and delete rates to a narrow document range) limit the ability of Cloud Firestore to scale. Review [Avoid hot-spots](https://cloud.google.com/firestore/mongodb-compatibility/docs/understand-reads-writes-scale#avoid_hotspots) 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](https://firebase.google.com/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. |