Docs Menu
Docs Home
/
MongoDB Manual
/

FAQ: MongoDB Storage

On this page

  • Storage Engine Fundamentals
  • Can you mix storage engines in a replica set?
  • Storage Recommendations
  • WiredTiger Storage Engine
  • Data Storage Diagnostics

This document addresses common questions regarding MongoDB's storage system.

A storage engine is the part of a database that is responsible for managing how data is stored, both in memory and on disk. Many databases support multiple storage engines, where different engines perform better for specific workloads. For example, one storage engine might offer better performance for read-heavy workloads, and another might support a higher throughput for write operations.

Tip

See also:

Storage Engines

Yes. You can have replica set members that use different storage engines (WiredTiger and in-memory)

Note

Starting in version 4.2, MongoDB removes the deprecated MMAPv1 storage engine.

Cluster performance might degrade once the combined number of collections and indexes reaches beyond 100,000. In addition, many large collections have a greater impact on performance than smaller collections.

Yes. See:

The ratio of compressed data to uncompressed data depends on your data and the compression library used. By default, collection data in WiredTiger use Snappy block compression; zlib and zstd compression is also available. Index data use prefix compression by default.

With WiredTiger, MongoDB utilizes both the WiredTiger internal cache and the filesystem cache.

Starting in MongoDB 3.4, the default WiredTiger internal cache size is the larger of either:

  • 50% of (RAM - 1 GB), or

  • 256 MB.

For example, on a system with a total of 4GB of RAM the WiredTiger cache uses 1.5GB of RAM (0.5 * (4 GB - 1 GB) = 1.5 GB). Conversely, on a system with a total of 1.25 GB of RAM WiredTiger allocates 256 MB to the WiredTiger cache because that is more than half of the total RAM minus one gigabyte (0.5 * (1.25 GB - 1 GB) = 128 MB < 256 MB).

Note

In some instances, such as when running in a container, the database can have memory constraints that are lower than the total system memory. In such instances, this memory limit, rather than the total system memory, is used as the maximum RAM available.

To see the memory limit, see hostInfo.system.memLimitMB.

By default, WiredTiger uses Snappy block compression for all collections and prefix compression for all indexes. Compression defaults are configurable at a global level and can also be set on a per-collection and per-index basis during collection and index creation.

Different representations are used for data in the WiredTiger internal cache versus the on-disk format:

  • Data in the filesystem cache is the same as the on-disk format, including benefits of any compression for data files. The filesystem cache is used by the operating system to reduce disk I/O.

  • Indexes loaded in the WiredTiger internal cache have a different data representation to the on-disk format, but can still take advantage of index prefix compression to reduce RAM usage. Index prefix compression deduplicates common prefixes from indexed fields.

  • Collection data in the WiredTiger internal cache is uncompressed and uses a different representation from the on-disk format. Block compression can provide significant on-disk storage savings, but data must be uncompressed to be manipulated by the server.

With the filesystem cache, MongoDB automatically uses all free memory that is not used by the WiredTiger cache or by other processes.

To adjust the size of the WiredTiger internal cache, see storage.wiredTiger.engineConfig.cacheSizeGB and --wiredTigerCacheSizeGB. Avoid increasing the WiredTiger internal cache size above its default value.

Note

The storage.wiredTiger.engineConfig.cacheSizeGB limits the size of the WiredTiger internal cache. The operating system uses the available free memory for filesystem cache, which allows the compressed MongoDB data files to stay in memory. In addition, the operating system uses any free RAM to buffer file system blocks and file system cache.

To accommodate the additional consumers of RAM, you may have to decrease WiredTiger internal cache size.

The default WiredTiger internal cache size value assumes that there is a single mongod instance per machine. If a single machine contains multiple MongoDB instances, then you should decrease the setting to accommodate the other mongod instances.

If you run mongod in a container (for example, lxc, cgroups, Docker, etc.) that does not have access to all of the RAM available in a system, you must set storage.wiredTiger.engineConfig.cacheSizeGB to a value less than the amount of RAM available in the container. The exact amount depends on the other processes running in the container. See memLimitMB.

To view statistics on the cache and eviction rate, see the wiredTiger.cache field returned from the serverStatus command.

Each connection uses up to 1 megabyte of RAM.

To optimize memory use for connections, ensure that you:

  • Monitor the number of open connections to your deployment. Too many open connections result in excessive use of RAM and reduce available memory for the working set.

  • Close connection pools when they are no longer needed. A connection pool is a cache of open, ready-to-use database connections maintained by the driver. Closing unneeded pools makes additional memory resources available.

  • Manage the size of your connection pool. The maxPoolSize connection string option specifies the maximum number of open connections in the pool. By default, you can have up to 100 open connections in the pool. Lowering the maxPoolSize reduces the maximum amount of RAM used for connections.

    Tip

    To configure your connection pool, see Connection Pool Configuration Settings.

Checkpoints
Starting in version 3.6, MongoDB configures WiredTiger to create checkpoints (i.e. write the snapshot data to disk) at intervals of 60 seconds. In earlier versions, MongoDB sets checkpoints to occur in WiredTiger on user data at an interval of 60 seconds or when 2 GB of journal data has been written, whichever occurs first.
Journal Data
WiredTiger syncs the buffered journal records to disk upon any of the following conditions:
  • For replica set members (primary and secondary members),

    • If there are operations waiting for oplog entries. Operations that can wait for oplog entries include:

    • Additionally for secondary members, after every batch application of the oplog entries.

  • If a write operation includes or implies a write concern of j: true.

    Note

    Write concern "majority" implies j: true if the writeConcernMajorityJournalDefault is true.

  • At every 100 milliseconds (See storage.journal.commitIntervalMs).

  • When WiredTiger creates a new journal file. Because MongoDB uses a journal file size limit of 100 MB, WiredTiger creates a new journal file approximately every 100 MB of data.

The WiredTiger storage engine maintains lists of empty records in data files as it deletes documents. This space can be reused by WiredTiger, but will not be returned to the operating system unless under very specific circumstances.

The amount of empty space available for reuse by WiredTiger is reflected in the output of db.collection.stats() under the heading wiredTiger.block-manager.file bytes available for reuse.

To allow the WiredTiger storage engine to release this empty space to the operating system, you can de-fragment your data file. This can be achieved using the compact command. For more information on its behavior and other considerations, see compact.

To view the statistics for a collection, including the data size, use the db.collection.stats() method from within mongosh. The following example issues db.collection.stats() for the orders collection:

db.orders.stats();

MongoDB also provides the following methods to return specific sizes for the collection:

The following script prints the statistics for each database:

db.adminCommand("listDatabases").databases.forEach(function (d) {
mdb = db.getSiblingDB(d.name);
printjson(mdb.stats());
})

The following script prints the statistics for each collection in each database:

db.adminCommand("listDatabases").databases.forEach(function (d) {
mdb = db.getSiblingDB(d.name);
mdb.getCollectionNames().forEach(function(c) {
s = mdb[c].stats();
printjson(s);
})
})

To view the size of the data allocated for each index, use the db.collection.stats() method and check the indexSizes field in the returned document.

If an index uses prefix compression (which is the default for WiredTiger), the returned size for that index reflects the compressed size.

The db.stats() method in mongosh returns the current state of the "active" database. For the description of the returned fields, see dbStats Output.

Back

GridFS