MongoDB explain plan visualizer & analyzer

No. Parsing and analysis run entirely in your browser using JavaScript. Your plan data is never transmitted to any server. Our advertising partners may collect standard browsing data (page views, ad interactions) per their own privacy policies — but your MongoDB plan is never part of that.

A COLLSCAN (collection scan) means MongoDB reads every document in the collection to satisfy the query — there is no index to narrow the search. On small collections this is fine, but at scale it means query time grows linearly with collection size. See how to read executionStats to interpret the numbers.

An IXSCAN (index scan) means MongoDB is using an index to locate matching documents. This is generally efficient, but efficiency depends on how selective the index is. A high keys-examined/returned ratio may indicate a poorly selective index — see IXSCAN and compound index scans for a before/after example.

This ratio measures how many documents MongoDB had to read to return each result. A ratio of 1:1 is ideal. A ratio of 1000:1 means MongoDB read 1000 documents to return 1. High ratios often point to missing or poorly selective indexes. See reading executionStats for interpretation guidance.

A covered query is satisfied entirely from index data without loading full documents from disk. totalDocsExamined: 0 is the signal — the analyzer flags this as a positive finding. See covered queries: examples and explain plans.

The tool handles explain output from MongoDB 4.x through 7.x. Classic and SBE (Slot-Based Execution) engine output are both recognised. Sharded cluster explains are partially supported — the tool flags the shape and shows raw JSON.

executionTimeMillis reflects the time of that specific explain run, which is affected by caching, server load, and working set. It is useful for relative comparison but should not be treated as a production latency guarantee.

Run db.collection.find({ field: value }).explain("executionStats") in the MongoDB shell, or db.collection.explain("executionStats").aggregate([...]) for aggregation pipelines. Copy the entire JSON output including the outer braces and paste it here.