The correct option is SQL API.

SQL API is the native document query model for Azure Cosmos DB and it supports a rich SQL like language for querying JSON documents with advanced filtering, aggregation functions such as COUNT, SUM, AVG and GROUP BY, JOINs across items, user defined functions and stored procedures. It also leverages Cosmos DB indexing and execution optimizations so it is most appropriate for running complex queries and aggregations across millions of documents.

MongoDB API is a compatibility layer that exposes the MongoDB wire protocol and it is useful for migrating MongoDB applications. It can perform aggregations with the MongoDB aggregation pipeline but it is not the native Cosmos DB query model and so it is less appropriate when the question asks for the most suitable API for advanced, native Cosmos DB querying and aggregations.

Table API is designed for key value and simple table storage scenarios and it does not provide the rich SQL like querying and aggregation features needed for complex analytical queries over JSON documents.

Gremlin API targets graph data and traversal queries and it is optimized for nodes and edges rather than document level aggregations, so it is not appropriate for running advanced filtering and aggregations across JSON documents.

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