Query caching in MongoDB isn’t configurable as it doesn’t support it natively.
MongoDB has a different approach to improving query performance, and this involves the use of indexes, sharding, and replication.
1. Indexing: It involves creating a special data structure that stores a small portion of the collection’s data set. MongoDB can use these indexes to limit the number of documents it must inspect to fulfill a read operation.
1. Replication: It involves a process of synchronizing data across multiple servers. MongoDB uses replication to increase data availability with multiple copies of data on different database servers.
1. Sharding: Sharding is a method for distributing data across multiple machines.
In addition, you can implement application level caching with tools like Redis or Memcached where results of frequent queries are stored for quicker access.
If the MongoDB deployment is a part of Atlas (MongoDB cloud), there is an integrated feature called Atlas Data Lake that can cache queries. You can check MongoDB Atlas documentation for more detailed instructions.
