Case study: Improving Miricanvas query performance with Amazon DocumentDB index optimization | Amazon Web Services

MiriCanvas, run by MiriD, hit query slowdowns after moving from MongoDB Atlas to Amazon DocumentDB.

Some indexes did not behave as expected, so the team redesigned partial indexes and reworked query patterns.

They split $or queries, replaced regex filters with range conditions, and improved performance.

The case shows that DocumentDB’s query planner and index behavior must be considered differently from MongoDB to keep large collaboration services fast and stable.