What mongoexport Actually Does (And When It Sucks)

mongoexport is MongoDB's tool for getting data out of collections in JSON or CSV format. Version 100.13.0 is current as of August 2025. It's decent for pulling data when you need it readable, but it's slow as hell on big collections and has some gotchas that'll bite you.

The truth is, mongoexport fills a specific niche - when you need human-readable data exports from MongoDB. But like a lot of MongoDB tooling, it works great until it doesn't, and then you're stuck debugging memory issues and performance problems that make you question your database choices.

What It Actually Does Well

JSON Format

JSON Export: Keeps your document structure intact with nested objects and arrays. Works fine for smaller collections when you need readable data for other applications or APIs that consume JSON format.

CSV Export: Flattens everything into spreadsheet format. Good luck if you have nested data - it turns into useless strings. But if you need to get data into Excel for some PM who insists on pivot tables, it works.

Query Filtering: You can use MongoDB query syntax with --query to export subsets. This actually saves your ass when you don't want to dump 50 million records just to get last week's data. The query operators work exactly like normal MongoDB finds.

Authentication: Supports the usual MongoDB auth methods including Atlas connections. At least it doesn't make you jump through hoops to connect securely via SSL/TLS.

When mongoexport Will Ruin Your Day

Large Collections: mongoexport will eat your RAM and crawl like a dying turtle on big datasets. We're talking 18 fucking hours for what should take 30 minutes. I've watched it choke and die on collections over 10 million docs while the server sits there with 15 idle CPU cores. This Stack Overflow thread is full of engineers losing their minds over 0.1% progress after 6 hours.

Memory Usage: It loads way more shit into memory than it should. Seriously, don't run this on a production box with limited RAM or you'll get this beauty: mongoexport: killed (signal 9) when the OOM killer decides your export isn't worth keeping alive. Understanding memory management becomes critical for large exports.

NOT for Backups: MongoDB screams this at you in the docs - don't use mongoexport for backups. It loses BSON type information. Use mongodump or your backup will be garbage when you try to restore it.

CSV Structure Issues: Nested objects become stringified JSON blobs in CSV. Arrays get flattened into comma-separated strings inside quoted fields. It's a mess if you have complex documents.

The bottom line: mongoexport is fine for quick data pulls and analysis on smaller datasets, but if you're working with production-scale collections or need reliable backups, you'll want to explore other options. Which brings us to how it stacks up against the competition...

mongoexport vs The Competition (Brutal Reality Check)

Feature

mongoexport

mongodump

Studio 3T Export

MongoDB Compass

Speed

Slow as hell

Fast enough

Decent but crashes randomly

Painfully slow for anything big

Output Format

JSON, CSV

Binary BSON

JSON, CSV, SQL, Excel

JSON, CSV

Data Type Preservation

❌ Destroys MongoDB types

✅ Keeps everything intact

⚠️ Sometimes works

❌ Same as mongoexport

Memory Usage

Eats RAM like crazy

Reasonable

Moderate

Reasonable

Query Filtering

✅ MongoDB syntax works

❌ All or nothing

✅ Nice GUI query builder

✅ GUI but limited

Authentication

Works with everything

Same as mongoexport

Connection strings

Built-in auth

Bulk Operations

❌ One collection at a time FML

Handles multiple collections

✅ Multiple collections

❌ One at a time

Cost

Free

Free

Expensive as shit ($199+/year)

Free

When It Crashes

Large collections, out of memory

Rarely

Randomly, especially on Windows

UI freezes constantly

Good For

Small data exports

Actual backups

Rich data analysis (if you pay)

Quick GUI exports

Avoid When

Big datasets, production backups

Data analysis needs

You're broke

Performance matters

Installation Reality and Production Gotchas

Getting It Installed (When It Actually Works)

mongoexport comes with the MongoDB Database Tools package, which is separate from the MongoDB server. This drives me nuts because older MongoDB versions used to include the tools.

Installation Methods (And Their Problems):

Package Managers: apt-get install mongodb-database-tools works sometimes. Half the time you get this shit:

E: Unable to locate package mongodb-database-tools

Or it installs version 4.2 from 2019 like some kind of joke. On macOS, brew install mongodb/brew/mongodb-database-tools actually works but takes 20 minutes to compile dependencies you don't need.

Direct Download: Download the pre-compiled binaries and drop them in your PATH environment variable. This is actually the safest bet, but you'll probably hit missing dependency hell on some Linux distros. Check the system requirements first.

Docker: Available in MongoDB's official Docker images, but debugging connection issues when everything's containerized is a pain in the ass.

Docker

Commands That Actually Work

Bash Commands

Basic Export (When Collection Isn't Huge):
mongoexport --collection=events --db=reporting --out=events.json

This uses all the default connection options to localhost:27017.

CSV Export with Specific Fields (CSV Flattening Will Ruin Complex Data):
mongoexport --db=users --collection=contacts --type=csv --fields=name,email,created_at --out=contacts.csv

The --fields option is required for CSV format. See the CSV formatting documentation for more pain.

Filtered Export (Actually Useful):
mongoexport --db=sales --collection=orders --query='{"status": "completed", "created": {"$gte": {"$date": "2025-01-01T00:00:00Z"}}}' --out=completed_orders.json

Production Reality (Where Everything Goes Wrong)

Linux Systems

Memory Will Kill You: mongoexport loads way more data into memory than it should. I've watched it crash with Killed (signal 9) on a 16GB server trying to export a collection that's only 2GB on disk. You'll see this in dmesg:

Out of memory: Kill process 15234 (mongoexport) score 901 or sacrifice child
Killed process 15234 (mongoexport) total-vm:12435788kB, anon-rss:11234567kB

The MongoDB forums are basically just people posting "why did mongoexport eat 24GB of RAM and crash?"

Pagination Is Your Only Hope: For big collections, chunk it with --skip and --limit. Sucks to script, but beats crashing:

## Export in 100k chunks - prepare to babysit this
mongoexport --skip=0 --limit=100000 --db=big --collection=data --out=data_1.json
mongoexport --skip=100000 --limit=100000 --db=big --collection=data --out=data_2.json

Connection Timeouts on Sharded Clusters: If you're hitting a sharded cluster, expect random connection drops on large exports. Use `--readPreference=secondary` to avoid hitting the primary, but prepare for this lovely error anyway:

2025-09-01T14:32:15.342+0000 E QUERY    [js] Error: error doing query: failed: 
network error while attempting to run command 'getMore' on host 'mongo-shard-02:27018'

Authentication Headaches: Put your credentials in a config file unless you want your MongoDB password in your shell history. Use --config=/path/to/config.yaml and lock down the file permissions properly.

After dealing with these installation and production headaches, you'll probably have questions. Trust me, everyone does. Here are the answers to the questions you'll inevitably ask after your first mongoexport disaster...

Questions People Actually Ask (With Honest Answers)

Q

How the hell do I export all collections from a database?

A

You can't. mongoexport only does one collection at a time and you have to specify the collection name. You'll need to script it or use mongodump for bulk operations. This limitation is stupid and annoying.

Q

Why is mongoexport so damn slow on my big collection?

A

Because it's a single-threaded piece of shit that was written in 2009 and hasn't learned about modern CPU architecture.

It'll max out one core while your other 15 cores sit there jerking off. I've literally watched htop show:```CPU[|||| 6.2%]

DB. Use --skip and --limit to chunk it, but each chunk will still crawl.

Q

Should I use mongoexport or mongodump for backups?

A

Don't use mongoexport for backups

  • it'll bite you in the ass. mongodump preserves BSON types, mongoexport destroys them. When you try to restore that "backup," your dates become strings and your NumberLongs become regular numbers. MongoDB literally tells you not to do this in their docs.
Q

How do I connect to MongoDB Atlas without my password showing up in bash history?

A

Use a config file: --config=/path/to/config.yaml with your credentials. Lock down the file permissions (chmod 600) because putting passwords on the command line is security 101 fail. The connection string would be: mongodb+srv://username:password@cluster.mongodb.net/database.

Q

Why does my CSV export look like garbage?

A

Because CSV flattening destroys document structure. Your nested objects become stringified JSON blobs, arrays become comma-separated strings inside quotes. It's a mess. If you have complex documents, stick with JSON or prepare to hate your life post-processing the CSV.

Q

Can I resume a failed export?

A

Hell no. mongoexport has zero resume capability. If it crashes halfway through your 50 million document export after running for 14 hours, you get to start over from document #1 and watch the progress bar crawl from 0% again. This is why you chunk with --skip and --limit

  • so when it inevitably fails, you only lose the current chunk and want to punch your monitor slightly less.
Q

Does mongoexport work with sharded clusters?

A

It works but expect timeouts and connection drops on large exports. Point it at your mongos instance but use --readPreference=secondary unless you want to hammer your primary. Prepare for random "not master" errors that'll make you question your life choices.

Q

Why can't I export this field with spaces in the name?

A

Use the exact field name in quotes with --fields="field name,other field,normal_field" or put the field list in a file with --fieldFile. Spaces and special characters in field names are a MongoDB design choice that haunts everyone forever.

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