"[MongoDB Atlas](https://www.mongodb.com/docs/atlas/) is a fully-managed cloud database available in AWS, Azure, and GCP. It has native support for \n",
"Vector Search on the MongoDB document data.\n",
"Use [MongoDB Atlas Vector Search](/docs/integrations/providers/mongodb_atlas) to semantically cache prompts and responses."
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"### `MongoDBCache`\n",
"An abstraction to store a simple cache in MongoDB. This does not use Semantic Caching, nor does it require an index to be made on the collection before generation.\n",
"Semantic caching allows users to retrieve cached prompts based on semantic similarity between the user input and previously cached results. Under the hood it blends MongoDBAtlas as both a cache and a vectorstore.\n",
"The MongoDBAtlasSemanticCache inherits from `MongoDBAtlasVectorSearch` and needs an Atlas Vector Search Index defined to work. Please look at the [usage example](/docs/integrations/vectorstores/mongodb_atlas) on how to set up the index.\n",
"To find more resources about using MongoDBSemanticCache visit [here](https://www.mongodb.com/blog/post/introducing-semantic-caching-dedicated-mongodb-lang-chain-package-gen-ai-apps)"