Adding MongoDB Atlas to examples of Vector Databases (#874)

authors.yaml

@@ -47,3 +47,8 @@ colin-openai:
   name: "Colin Jarvis"
   website: "https://twitter.com/colintjarvis"
   avatar: "https://pbs.twimg.com/profile_images/1647875178947387393/aUc7D9m-_400x400.jpg"
+
+prakul:
+  name: "Prakul Agarwal"
+  website: "https://www.linkedin.com/in/prakulagarwal"
+  avator: "https://media.licdn.com/dms/image/D5603AQEUug83qKgRBg/profile-displayphoto-shrink_800_800/0/1675384960197?e=1706140800&v=beta&t=qxkDbBr-Bk2ASpcwbR5JVPD6yS-vzmIwNHAa8ApyDq4"

examples/vector_databases/mongodb_atlas/README.md

@@ -0,0 +1,6 @@
+# MongoDB Atlas Vector Search
+
+
+[Atlas Vector Search](https://www.mongodb.com/products/platform/atlas-vector-search) is a fully managed service that simplifies the process of effectively indexing high-dimensional vector data within MongoDB and being able to perform fast vector similarity searches. With Atlas Vector Search, you can use MongoDB as a standalone vector database for a new project or augment your existing MongoDB collections with vector search functionality. With Atlas Vector Search, you can use the powerful capabilities of vector search in any major public cloud (AWS, Azure, GCP) and achieve massive scalability and data security out of the box while being enterprise-ready with provisions like FedRamp, SoC2 compliance.
+
+Documentation - [link](https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-overview/)