"How to optimize query performance in Azure Cosmos DB with large JSON documents?"

Question

I'm using Azure Cosmos DB (SQL API) to store large JSON documents (each ~1MB in size). I'm experiencing high RU consumption and latency during queries, especially when filtering on nested properties.

Could you please suggest the best practices to:

Improve query performance with large documents

Use indexing effectively in this case.Also, is it advisable to denormalize or split the data into multiple smaller documents for better efficiency?

Answer 1

Hi @ Ananth Sharma

Handling large JSON documents in Azure Cosmos DB can be tricky, but there are ways to improve query performance and reduce RU usage:

Indexing Smartly: Customize indexing to exclude unnecessary properties. Use composite indexing if filtering on multiple fields.

Better Queries: Avoid SELECT *, filter on indexed properties, and use pagination to handle large results efficiently.

Partitioning Matters: Pick a partition key that spreads data evenly to avoid hot partitions. Try to keep queries within a single partition.

Data Structure: If you often need full documents, denormalization could help. If you only query parts of the document, splitting into smaller ones might work better.

You can check out Microsoft's guide for more details.

Hope this helps. Do let us know if you any further queries.

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