The Tool Desk
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Why mongorestore can exhaust a VPS
A dump’s file size does not tell you the peak RAM required to restore it. An official MongoDB Jira report describes a restore of approximately 50 GB of dump data reaching as much as 76 GB of system memory. That is a reported case, not a sizing formula, but it demonstrates why a compressed archive or BSON total cannot be treated as a safe RAM estimate.
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Peak usage depends on the data being restored, the Database Tools and server versions, how many collections are active at once, how many insertion workers are operating per collection, index work, available disk space, and limits imposed by the VPS provider. A restore can therefore fail on a machine whose disk comfortably holds the dump.
On a small VPS, the most useful first change is to reduce simultaneous work. MongoDB documents a default of four parallel collections and one insertion worker per collection. Those defaults can create a larger simultaneous workload than a constrained machine can sustain.
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What the mongorestore concurrency options mean
| Option | Documented default | What it controls | Conservative VPS value |
|---|---|---|---|
--numParallelCollections |
4 | How many collections can be restored concurrently. | 1 |
--numInsertionWorkersPerCollection |
1 | Concurrent insert operations used for each collection. | 1 |
-j |
Context-dependent | For a single-collection restore, it maps to insertion workers rather than parallel collections. | Prefer the explicit insertion-worker option. |
The explicit flags remove ambiguity, especially when the dump contains only one collection. Begin with:
mongorestore --numParallelCollections=1 --numInsertionWorkersPerCollection=1 /path/to/dumpDo not assume that increasing -j will make a single-collection restore use more collection-level parallelism. In that case it changes insertion-worker concurrency, which can increase the simultaneous workload on the VPS.
A recovery procedure for an out-of-memory restore
1. Record the tool and server versions
Before changing several variables at once, record the versions involved:
mongorestore --version
mongosh --eval 'db.version()'The current MongoDB Database Tools documentation identifies version 100.19.1. Use the version actually installed on your VPS and verify that it is compatible with the MongoDB server and the dump format. A version mismatch is not fixed by lowering parallelism, so keep it as a separate diagnostic variable.
2. Re-run with one collection and one insertion worker
Use both explicit options on the first retry:
mongorestore
--numParallelCollections=1
--numInsertionWorkersPerCollection=1
/path/to/dumpThis deliberately trades restore speed for a smaller simultaneous workload. Let that run establish a baseline for elapsed time and peak memory before experimenting with higher values.
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3. Restore only the namespaces you need
If the dump contains data that can be restored later, reduce the amount handled in one operation. To include one namespace:
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--numParallelCollections=1
--numInsertionWorkersPerCollection=1
--nsInclude='db.collection'
/path/to/dumpTo exclude a database or collection pattern:
mongorestore
--numParallelCollections=1
--numInsertionWorkersPerCollection=1
--nsExclude='db.unneeded*'
/path/to/dumpNamespace filters let you divide a large restore into measured units. Restore one database or collection, record its memory peak and duration, then proceed to the next unit.
4. Decide whether to defer index restoration
--noIndexRestore prevents indexes from being restored during the data load:
mongorestore
--numParallelCollections=1
--numInsertionWorkersPerCollection=1
--noIndexRestore
/path/to/dumpThis can reduce immediate restore work, but it does not eliminate index creation. You must schedule and monitor index creation later, preferably during a maintenance window with enough memory, disk space, and recovery time. Use this option only when the application can remain offline or operate without those indexes until they are rebuilt.
5. Match the input-format flags to the dump
Use --gzip when the dump files are gzip-compressed and --archive when the input is an archive:
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mongorestore --gzip /path/to/compressed-dump
mongorestore --archive=/path/to/dump.archiveThese options tell mongorestore how to read the input. They are not guaranteed memory fixes. Selecting the wrong format can produce an error or an unusable restore, while selecting the correct format does not establish how much RAM the operation will need.
6. Measure memory while the restore runs
Measure the process and the VPS rather than guessing from the dump’s size. In a second shell, identify the process and inspect resident memory:
pgrep -af mongorestore
ps -o pid,ppid,%mem,rss,vsz,etime,cmd -p <PID>
free -h
vmstat 1rss is the process’s resident memory in kilobytes. Watch whether available memory keeps falling, whether swap activity rises, and whether the operating system or provider terminates the process. Stop unrelated jobs such as builds, game servers, scheduled backups, or monitoring workloads for the duration of the restore so they do not compete for the same limit.
Record at least:
- the command and all concurrency flags;
- the highest observed resident memory for
mongorestore; - the VPS’s available memory and swap activity;
- elapsed time and the namespace being restored;
- whether the process completed, was killed, or failed with a database error.
7. Add capacity only after measuring
If the measured working set still exceeds the VPS limit with one collection and one insertion worker, reducing concurrency further is not possible through those two settings. At that point, move the restore to a higher-memory plan or another machine. Provider-supported swap can provide a temporary buffer, but it is slower than RAM and does not turn an undersized VPS into a predictable restore host.
Do not assign a universal RAM number to every dump. The required capacity is specific to the dataset shape, indexes, tool and server versions, storage performance, and the provider’s memory and process limits.
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How to tune concurrency without repeating the failure
Once a one-by-one restore is stable, increase only one setting at a time. A practical sequence is:
- Restore a representative database or collection with
--numParallelCollections=1 --numInsertionWorkersPerCollection=1. - Record peak resident memory, available memory, duration, and whether the server remained responsive.
- If there is substantial memory headroom, raise
--numInsertionWorkersPerCollectionby one and repeat the same workload. - Only after insertion-worker changes are understood, test
--numParallelCollections=2on a measured subset. - Stop increasing values when the VPS approaches its memory limit, begins heavy swapping, becomes unresponsive, or the restore is killed.
This is operational guidance, not a MongoDB performance benchmark. The safe value for one VPS may be unsafe for another even with the same dump, because the operating system, database server, and other services consume memory too.
Choosing among the main fixes
| Fix | Peak resident memory | Restore duration | Disk and maintenance impact | Risk if the process is killed |
|---|---|---|---|---|
| Set one parallel collection and one insertion worker | Normally lower simultaneous workload | Normally longer | No extra index-maintenance step | Smaller operation units are easier to retry |
| Use namespace include/exclude filters | Lower for each individual operation | Longer overall if many operations are needed | Requires a restore plan for omitted namespaces | A failed unit does not necessarily invalidate completed units |
Use --noIndexRestore |
May reduce immediate restore work | Data load may finish sooner, but index work is postponed | Requires later index creation and its own disk and memory window | Application performance or availability can suffer until indexes exist |
| Use provider-supported swap | Provides a buffer when RAM is exhausted | Usually slower than RAM, especially under sustained pressure | Consumes configured swap space | Heavy swapping can make the host unresponsive before completion |
| Move to a higher-memory VPS | Raises the available ceiling | May permit safer concurrency, but is not a guarantee | Changes infrastructure cost and limits | Still requires measurement and a retry plan |
Evaluate every change against four questions: what happens to peak resident memory, how long will the restore take, how much temporary or index-related disk work is required, and what can be recovered if the process is killed?
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Symptoms and what they usually indicate
The process is killed without a useful mongorestore error
An operating-system or provider memory limit may have terminated it. Check system logs and the VPS control panel if available, then repeat with both concurrency settings set to one. A clean application-level error is not required for an out-of-memory kill.
Memory rises when several collections start together
Keep --numParallelCollections=1. The documented default is four, so explicitly setting one matters on a small machine even when insertion workers remain at their default of one.
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A single collection still consumes too much memory
Keep the collection-level setting at one and explicitly set --numInsertionWorkersPerCollection=1. Split the restore with --nsInclude if the dump contains other data, defer indexes when operationally acceptable, and measure the resulting working set. If that single-collection operation still exceeds the VPS limit, resize or move the restore rather than repeatedly retrying the same command.
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The restore succeeds but the application is slow afterward
If indexes were deferred, schedule their creation and verify them before returning normal traffic. A successful data load is not proof that the database has the indexes the application expects.
The command reports an input or archive error
Check whether the dump is a directory of compressed files or an archive, then use the matching --gzip or --archive option. Format flags select how the input is read; changing them should not be presented as a general memory remedy.
Planning a low-RAM restore
- Keep enough free disk for the dump, the restored data, temporary work, and any later index creation. RAM reduction does not remove storage requirements.
- Schedule the restore when unrelated workloads can be stopped and when you can observe the process continuously.
- Use a test subset or one namespace first, then capture a measured peak before committing to the complete restore.
- Preserve the exact command, tool version, server version, and outcome for each attempt so a retry changes one variable at a time.
- Have a recovery plan for an interrupted operation, including whether you will clean up partial data, restore into a new database, or repeat a namespace after verifying what completed.
When should you resize the VPS?
Resize when a measured, deliberately serialized restore still needs more memory than the provider makes available, or when swapping makes the operation unreliable. The 50-GB dump and 76-GB system-memory report is evidence that large differences between dump size and peak memory can occur; it is not a promise that your dump needs 76 GB or that a particular VPS size will work.
A higher-memory machine should be selected from measurements of your own dataset, plus headroom for the MongoDB server, operating system, indexes, and other required services. After moving, retain the one-at-a-time baseline and increase concurrency only if the new host remains stable.
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A repeatable command template
Use this as a starting point, replacing the path and optional namespace filter with values appropriate to your restore:
mongorestore
--numParallelCollections=1
--numInsertionWorkersPerCollection=1
--nsInclude='db.collection'
/path/to/dumpRemove --nsInclude when restoring the complete dump. Add --gzip for compressed dump files or use --archive=/path/to/dump.archive for archive input. Add --noIndexRestore only when you have a documented window and procedure for creating the indexes afterward.
Bottom line for a constrained VPS
Start with explicit serialization: --numParallelCollections=1 --numInsertionWorkersPerCollection=1. Restore only the namespaces you need, consider deferring indexes, and observe resident memory and available memory throughout the run. Increase one concurrency setting only after a measured subset completes. If the serialized working set still exceeds the VPS limit, use a higher-memory host; swap is only a slower buffer, not a substitute for capacity planning.
Quick Recap
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