Monghoul against MongoDB Compass

We make one of these, so start with the conclusion you would not expect from us: most people reading this should use Compass. It is free, it is made by the people who make the database, and it will still be here in ten years. If your work is reading documents and building the occasional pipeline, nothing below will change your week.

What follows is what the difference actually is, measured rather than asserted, and where Compass wins anyway.

Which one to pick

Pick Compass if you mostly read documents and build the occasional pipeline, if you want a tool that will still exist in ten years, or if you need the Readonly or Isolated editions to get through a security review.

Pick us if the client stays open all day, if you write aggregations for a living, or if an assistant holds the connection and you want the write guard running at the driver rather than over the query text.

What was measured

The method is stated above. These are the numbers it produced.

The spread across the seven runs was small enough to be uninteresting: Compass 1.224 to 1.307 s and 317 to 326 MB, Monghoul 0.070 to 0.089 s and 396 to 418 MB.

Reading those numbers honestly

Time is to a window appearing, not to being ready for a query. The script waits for the app to own a window handle. That is a fair thing to compare and it is not the same as “you can start working”, and the gap between those two is not necessarily the same for both. Do not read 18x as how much sooner you get useful work done.

Compass holds less memory than we do. 321 MB against 398 MB. Both render in a browser engine and neither is a terminal, and on this row the official client is the leaner one.

Counted the naive way, that row would read 631 MB against 749 MB, because summing working set charges an eight-process app once per process for pages that exist once. Both figures are inflated and so is the gap between them: only the ratio roughly holds.

The disk difference is structural rather than sloppy. Compass ships a Chromium runtime: the measurement found five artifacts that only exist in a bundled browser, libEGL, libGLESv2, d3dcompiler, icudtl and ffmpeg.dll. Monghoul found none of them, because it uses the WebView2 already on the machine. That is the Electron against Tauri difference, and it is worth saying that this is a trade rather than a free win: bundling the browser means Compass renders identically on every machine, and using the system one means we inherit whatever WebView2 the OS has.

Monghoul’s 105.6 MB is also two things, not one: a 17.8 MB shell and an 87.7 MB Bun sidecar that runs the queries.

Where Compass wins, and it is not close

It is free, entirely. On 7 September 2026 there was no paid tier, no connection limit and no trial. We cannot promise anything about another company’s future pricing and will not pretend to, but nothing about MongoDB’s position suggests a change here.

It ships two editions nobody else does. A Readonly Edition with write and delete removed from the binary, and an Isolated Edition whose only network connection is to your MongoDB instance. Both were listed on the download page on 7 September 2026; check their release notes before you build a policy on either, because edition line-ups do change. Both are far easier to take to a security review than any setting, because a setting can be changed back and a missing code path cannot. If you work somewhere that asks those questions, this is a real argument and we do not have an answer to it.

It is the reference implementation. New server features arrive there first, and it is maintained by the company that decides what the server does. Betting against that is not a good long-term bet for a tool you use every day.

It will exist in ten years. We are one year old. That asymmetry is not something a benchmark can close, and if longevity is what you are buying then this is the honest answer.

The five things we put the work into

Compass is the reference client and covers the whole server. These five are where we went further, and the last one is the only one a stopwatch can prove.

Autocomplete bound to your data

Completions come from the active database’s analyzed field paths, field types and enum values, so a field’s known values appear where a value for that field belongs and nowhere else. Position decides what is offered: query operators inside a $match, expressions inside a computed projection, the JSON Schema vocabulary inside $jsonSchema, and an operator’s own option keys inside its body with the required ones first. The full behaviour.

Write protection enforced at the driver

Per connection, scoped to everything or to named databases and collections, and checked as the call runs rather than by scanning the query text. Compass answers this differently and in one respect better, with a Readonly Edition that has the write path removed from the binary. A missing code path beats any runtime check, ours included. Where that check runs decides what it catches.

MCP, rather than a prompt box

Compass generates queries from natural language inside the app. We expose the app to the assistant you already use, as 70+ MCP tools behind a token, with the reachable connections chosen before the server starts. How that is set up.

The window

11 themes, a command palette, rebindable shortcuts, tabs that persist across sessions and can be split or detached, and results as a list, a tree or a table. Compass is built to cover everything the server does; this is built to stay out of the way while you do one thing.

Speed

0.07 seconds to a window against 1.26, and 105.6 MB installed against 650.6 MB. Compass ships a Chromium and we use the WebView2 Windows already has, and the table above is what that buys.

Capability by capability

The Compass column comes from MongoDB’s own product page, read on 13 September 2026. Compass 1.50.0 was installed and measured for the table further up, but its capabilities were not driven one by one, so a cell here says what the product page covers rather than what the application lacks. Undocumented is not the same as absent. Both tools cover the basics, so only the rows where they differ are listed.

The read-only row is the one to read twice, for the reason given above.

What this page does not tell you

Nothing here is about how good either one is to use. Autocomplete quality, whether the aggregation builder actually helps, behaviour against a slow or unhealthy cluster: none of that is in the table, because none of it can be measured with a stopwatch. The numbers above are the cheap facts, and cheap facts are worth exactly what they cost.

The way to settle the rest is to install both and point them at the same database for a week. Compass costs nothing, and ours has a free tier with no signup and no time limit, so that comparison costs an afternoon and no money.

If you came here looking for a Compass alternative

Most people who search for one are asking about startup and memory, and the table above is that answer with a script behind it. If what sent you here was SQL migration or single sign-on, the tool you want is Studio 3T rather than us. If it was a read-only build you can take to a security review, Compass already has the best answer in this category and we say so above.

Reproducing the numbers

git clone https://github.com/Kontsedal/monghoul-public
cd monghoul-public/benchmarks/client-footprint
.\measure.ps1 -Runs 7 -Only 'Compass|Monghoul'

It force-stops matching processes between runs, so close anything you care about first. The paths at the top of the script assume a per-user install of each app and will need adjusting otherwise.