MongoDB Pipeline Visualizer

The visualizer supports all commonly used aggregation stages including $match, $group, $project, $lookup, $unwind, $sort, $limit, $skip, $addFields, $set, $replaceRoot, $merge, $out, $facet, $bucket, $sample, and $count. Paste any valid aggregation pipeline array and the tool will parse and visualize each stage automatically.

The tool tracks which document fields exist at each pipeline stage. For example, a $project stage removes unlisted fields, a $group stage replaces all fields with _id and accumulator outputs, a $lookup adds a new array field, and $unwind converts an array field to individual documents. You can see fields added (green), removed (red), and modified (yellow) at every step.

The smart warnings engine detects common MongoDB pipeline mistakes: placing $match after $lookup instead of before (missing index optimization), running $sort without a preceding $match (full collection scan), using $group without $match (processes entire collection), $lookup without $unwind (returns arrays that may be unexpected), and placing $out or $merge before the last stage. These warnings help you write more efficient pipelines.

Yes. The $lookup stage is displayed as a distinct node showing the foreign collection, local and foreign fields, and the output array name. The tool also warns if you forget to $unwind the lookup result, which is a common mistake that leads to array-of-arrays issues in subsequent stages.

Yes. $facet stages are parsed and displayed showing the parallel sub-pipelines. The tool can detect issues within nested pipelines and warns about potential performance concerns when $facet processes large result sets.

No. All parsing, visualization, and analysis happen entirely in your browser using JavaScript. Your pipeline JSON never leaves your device — no server calls, no uploads, no data collection. This is critical for developers working with pipelines containing sensitive collection names, field names, or business logic. Verify this in your browser DevTools Network tab.

Yes. You can export the visual pipeline diagram as PNG (high-DPI, 2x resolution) or SVG. This is useful for documentation, code reviews, or sharing with your team in Notion, Slack, or Confluence.

Copy your aggregation pipeline array (the part inside db.collection.aggregate([...])) and paste it into the input field. The tool expects a valid JSON array of stage objects. If your pipeline uses MongoDB Extended JSON syntax (like $date or NumberLong), simplify those values to standard JSON strings or numbers before pasting.