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When mongorestore exhausts a VPS, reduce restore concurrency before adding RAM. Set both collection and insertion parallelism to one, restore only the namespaces you need, and defer index creation if appropriate. Then measure the process’s resident memory and the VPS’s available memory. Dump-file size alone cannot predict the required RAM: MongoDB has documented a roughly 50 GB dump reaching 76 GB of system memory during restore.
Why mongorestore runs out of memory
mongorestore does more than read a dump sequentially from disk. It must decode input, prepare batches of documents, send concurrent insert operations, and optionally recreate indexes. Several collections can be processed at once, and each collection can have insertion workers. The simultaneous working set is therefore affected by collection count, document shape, indexes, compression, storage speed, and the versions of the tools and server.
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On a VPS, an out-of-memory failure may appear as a terminated process, an SSH session that reports “Killed,” a provider alert, or a Linux out-of-memory event. The first response should be to reduce the amount of work happening simultaneously, not to assume that changing compression or archive format will solve the problem.
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Check versions and capture a baseline
Record the Database Tools version
Before changing flags, run:
mongorestore --versionMongoDB’s current documentation page lists Database Tools version 100.19.1. Your installed executable may be older, and option behavior or compatibility can differ between tool and server releases. Record the MongoDB server version as well, then verify that the selected Database Tools release is supported for that server.
Measure memory before the restore
Capture the VPS’s normal memory state and keep a second terminal open during the operation:
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watch -n 2 free -hUse your provider’s monitoring panel if it reports memory pressure or swap activity. On Linux, you can identify the process and observe its resident set size with the tools available on your distribution:
pgrep -af mongorestore
ps -o pid,rss,vsz,cmd -p <PID>RSS is the process’s resident memory in the units shown by ps; compare its growth with the VPS’s available memory, not just the dump’s file size. Stop unrelated jobs, scheduled backups, and build tasks while collecting a baseline so they do not consume the headroom needed by the restore.
Set mongorestore parallelism explicitly
Use one collection and one insertion worker first
MongoDB documents a default of 4 for --numParallelCollections and a default of 1 for --numInsertionWorkersPerCollection. On a constrained VPS, start with both values set to one:
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mongorestore
--numParallelCollections=1
--numInsertionWorkersPerCollection=1
/path/to/dump--numParallelCollections=1 prevents multiple collections from being restored concurrently. --numInsertionWorkersPerCollection=1 limits concurrent insert operations inside the collection currently being restored. The second setting is already the documented default, but specifying it makes the intended limit clear and protects the command if a wrapper, script, or future change supplies a different value.
Understand what -j changes
For a single-collection restore, -j maps to insertion workers rather than the number of collections restored in parallel. Do not use a short option when you need to control both dimensions. Keep the explicit long options in the command so an operator reviewing the command can see exactly which concurrency limits are active.
Increase only one setting at a time
Once a one-by-one restore completes reliably, raise one concurrency setting by one step, measure peak resident memory and elapsed time, and run another representative restore. If memory pressure returns, revert the last change. This incremental procedure is operational guidance based on the documented controls, not a MongoDB performance benchmark; the safe values depend on your data and provider limit.
Restore only the data you need
Include selected namespaces
A full dump is not always required for the immediate recovery. Restrict the operation to a required collection with a namespace include filter:
mongorestore
--numParallelCollections=1
--numInsertionWorkersPerCollection=1
--nsInclude='app.orders'
/path/to/dumpUse the database and collection name in the filter. Restore additional collections in separate commands if that keeps the working set below the VPS limit.
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Exclude data that can wait
When most of a dump is needed but a known set can be postponed, use an exclusion filter:
mongorestore
--numParallelCollections=1
--numInsertionWorkersPerCollection=1
--nsExclude='app.unneeded*'
/path/to/dumpPlan the later restore explicitly and keep a record of which namespaces were omitted. Namespace filtering lowers the amount handled in one operation; it does not change the memory characteristics of a single very large collection.
Decide whether to defer index restoration
Use --noIndexRestore when the maintenance window allows it
MongoDB documents --noIndexRestore as preventing indexes from being restored. A constrained restore can therefore load documents first:
mongorestore
--numParallelCollections=1
--numInsertionWorkersPerCollection=1
--noIndexRestore
/path/to/dumpThis option does not eliminate index work. You must create the required indexes later, during a controlled maintenance window, and monitor the additional disk, CPU, elapsed time, and memory they consume. Do not put a no-index restore into production traffic until the application’s required indexes have been recreated and checked.
When postponing indexes is the wrong trade-off
If the restored database must immediately serve queries whose correctness or latency depends on indexes, skipping them may create an operational outage of a different kind. In that case, retain index restoration, keep concurrency at one, and schedule enough time and disk capacity for the index phase.
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Use the correct input flags
Compressed dump files
Use --gzip when the dump files were produced in the compressed format expected by mongorestore:
mongorestore
--gzip
--numParallelCollections=1
--numInsertionWorkersPerCollection=1
/path/to/compressed-dumpArchive input
Use --archive for archive input, supplying the archive path as appropriate for your command:
mongorestore
--archive=/path/to/backup.archive
--numParallelCollections=1
--numInsertionWorkersPerCollection=1These flags tell the tool how to read the input. They are not guaranteed memory fixes. If the same data is restored with lower concurrency, the concurrency change—not merely the fact that the input is compressed or archived—is the relevant memory test.
Compare the available remedies
| Remedy | Peak resident memory | Restore duration | Disk and temporary work | Recovery risk if killed |
|---|---|---|---|---|
| Set collection parallelism to 1 | Usually lowers simultaneous collection work; exact reduction is dataset-specific | Usually longer than the default of 4 | Does not remove storage needed by the data or indexes | Lower concurrency can make a restart more manageable, but a killed process still requires validation |
| Set insertion workers to 1 | Limits concurrent insert operations within a collection | May increase elapsed time for large collections | Does not by itself reduce the dump size | Fewer simultaneous operations can simplify troubleshooting |
| Use namespace filters | Reduces the data handled in one operation | Several smaller restores may take longer overall | Allows staged use of available disk and memory | Requires a written list of restored and deferred namespaces |
Use --noIndexRestore |
Defers index-related work; the eventual index build still needs resources | Shorter initial phase, followed by a separate index phase | Index creation still needs disk space and a maintenance window | Database may be incomplete for applications until indexes are rebuilt |
| Add provider-supported swap | Provides a slower buffer when RAM is exhausted; it does not increase physical RAM | Can be substantially slower once the workload swaps | Consumes provider disk and may compete with the restore | May prevent an immediate kill, but cannot make an over-sized workload safe or fast |
| Move to a higher-memory VPS | Raises the available limit to match the measured working set | Can avoid extreme swapping and reduce elapsed time | Depends on the provider’s storage and plan limits | Does not correct incompatible versions or a malformed restore command |
The comparison is about trade-offs, not fixed performance promises. Measure peak memory and duration on your own dataset before selecting a permanent setting.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Know when the VPS is simply too small
After reducing both concurrency settings, filtering unnecessary namespaces, and deciding how to handle indexes, observe a representative restore. If the measured working set still exceeds the VPS memory limit, a larger plan is the direct fix. There is no universal RAM number for a MongoDB restore: the answer depends on dataset shape, document and index characteristics, Database Tools and server versions, storage behavior, and the provider’s memory and swap limits.
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Provider-supported swap can supply a short-term buffer, but it is slower than RAM. Treat it as protection against an immediate failure, not as a substitute for right-sizing a recurring restore. Confirm that the provider permits and supports swap before enabling it, and watch disk capacity and I/O pressure while the restore runs.
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Recover safely after a killed restore
Do not assume completion
A process that exits from memory pressure may have restored some namespaces and stopped during another. Record the command, the last visible collection, the process exit status, and the memory readings. Check the target database and compare the restored namespace list with the backup inventory before declaring success.
Resume in controlled units
Use --nsInclude to restore remaining databases or collections separately. Smaller units make it possible to identify the collection that causes the pressure and to measure each unit’s peak memory. Decide how to handle partially loaded collections according to your recovery plan; do not blindly rerun a command against production data without determining whether duplicate or incomplete records are possible in your workflow.
Validate before reopening traffic
- Confirm that every required namespace was restored.
- Check representative document counts and application-level records.
- Verify that required indexes exist, especially if
--noIndexRestorewas used. - Review MongoDB logs and provider alerts for errors during the restore.
- Keep the measured peak memory and elapsed time with the recovery record for the next incident.
A repeatable low-memory restore procedure
- Identify the versions. Run
mongorestore --version, record the MongoDB server version, and check compatibility. MongoDB’s current documentation lists Database Tools 100.19.1. - Prepare the VPS. Stop unrelated memory-intensive jobs, confirm available disk space, and open a monitoring session for available memory, swap, and the restore process’s resident memory.
- Choose the input mode. Add
--gzipfor compressed dump files or--archivefor archive input. Do not treat either option as a memory remedy. - Start conservatively. Run with
--numParallelCollections=1and--numInsertionWorkersPerCollection=1. - Limit scope. Apply
--nsIncludeor--nsExcludewhen the full dump is not needed in one operation. - Choose index timing. Add
--noIndexRestoreonly when you have a documented maintenance window and a plan to recreate and verify indexes. - Measure the result. Record peak resident memory, available memory, elapsed time, disk usage, and any errors.
- Adjust carefully. If the VPS remains stable, increase only one concurrency setting for the next unit. If it does not, keep the lower setting or move the restore to a higher-memory environment.
- Validate. Check namespaces, representative data, indexes, and application behavior before considering the recovery complete.
Common mistakes that prolong the outage
- Relying on dump size. A 50 GB dump has been reported using up to 76 GB of system memory during restore, so file size is not a safe RAM estimate.
- Changing only
-j. For a single collection, that short option controls insertion workers; it does not clearly express the collection-parallelism limit. - Assuming compression fixes memory.
--gzipchanges input handling, not the amount of concurrent restore work. - Skipping indexes without a plan.
--noIndexRestoredefers index work; it does not remove the requirement to build and monitor those indexes. - Increasing every setting at once. You lose the ability to identify which change caused the memory spike and make rollback harder.
- Ignoring provider limits. A VPS can have less usable memory than its advertised total after the operating system and other services are accounted for.
Bottom line for a memory-constrained VPS
Begin with an explicit one-by-one restore: --numParallelCollections=1 --numInsertionWorkersPerCollection=1. Filter namespaces when possible, defer indexes only with a controlled follow-up plan, and use the correct input flag for gzip or archive data. Monitor the actual working set rather than guessing from dump size. If the measured requirement remains above the VPS limit, a larger-memory environment is the dependable solution; swap may provide a slower safety margin but cannot replace sufficient RAM.
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