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MongoDB Manual

MongoDB Limits and Thresholds

On this page

  • MongoDB Atlas Limitations
  • BSON Documents
  • Naming Restrictions
  • Naming Warnings
  • Namespaces
  • Indexes
  • Sorts
  • Data
  • Replica Sets
  • Sharded Clusters
  • Operations
  • Sessions

This document provides a collection of hard and soft limitations of the MongoDB system. The limitations on this page apply to deployments hosted in all of the following environments unless specified otherwise:

  • MongoDB Atlas: The fully managed service for MongoDB deployments in the cloud

  • MongoDB Enterprise: The subscription-based, self-managed version of MongoDB

  • MongoDB Community: The source-available, free-to-use, and self-managed version of MongoDB

The following limitations apply only to deployments hosted in MongoDB Atlas. If any of these limits present a problem for your organization, contact Atlas support.

Shards in multi-region clusters
Shards in single-region clusters
Cross-region network permissions for a multi-region cluster
40. Additionally, a cluster in any project spans more than 40 regions, you can't create a multi-region cluster in this project.
Electable nodes per replica set or shard
Cluster tier for the Config server (minimum and maximum)

MongoDB Atlas limits concurrent incoming connections based on the cluster tier and class. MongoDB Atlas connection limits apply per node. For sharded clusters, MongoDB Atlas connection limits apply per mongos router. The number of mongos routers is equal to the number of replica set nodes across all shards.

Your read preference also contributes to the total number of connections that MongoDB Atlas can allocate for a given query.

MongoDB Atlas has the following connection limits for the specified cluster tiers:

MongoDB Atlas Cluster Tier
Maximum Connections Per Node
MongoDB Atlas Cluster Tier
Maximum Connections Per Node
MongoDB Atlas Cluster Tier
Maximum Connections Per Node


MongoDB Atlas reserves a small number of connections to each cluster for supporting MongoDB Atlas services.

If you're connecting to a multi-cloud MongoDB Atlas deployment through a private connection, you can access only the nodes in the same cloud provider that you're connecting from. This cloud provider might not have the primary node in its region. When this happens, you must specify the secondary read preference mode in the connection string to access the deployment.

If you need access to all nodes for your multi-cloud MongoDB Atlas deployment from your current provider through a private connection, you must perform one of the following actions:

  • Configure a VPN in the current provider to each of the remaining providers.

  • Configure a private endpoint to MongoDB Atlas for each of the remaining providers.

While there is no hard limit on the number of collections in a single MongoDB Atlas cluster, the performance of a cluster might degrade if it serves a large number of collections and indexes. Larger collections have a greater impact on performance.

The recommended maximum combined number of collections and indexes by MongoDB Atlas cluster tier are as follows:

MongoDB Atlas Cluster Tier
Recommended Maximum
5,000 collections and indexes
M20 / M30
10,000 collections and indexes
100,000 collections and indexes

MongoDB Atlas deployments have the following organization and project limits:

Database users per MongoDB Atlas project
Atlas users per MongoDB Atlas project
Atlas users per MongoDB Atlas organization
API Keys per MongoDB Atlas organization
Access list entries per MongoDB Atlas Project
Users per MongoDB Atlas team
Teams per MongoDB Atlas project
Teams per MongoDB Atlas organization
Teams per MongoDB Atlas user
Organizations per MongoDB Atlas user
Linked organizations per MongoDB Atlas user
Clusters per MongoDB Atlas project
Projects per MongoDB Atlas organization
Custom MongoDB roles per MongoDB Atlas project
Assigned roles per database user
Hourly billing per MongoDB Atlas organization
Federated database instances per MongoDB Atlas project
Total Network Peering Connections per MongoDB Atlas project
50. Additionally, MongoDB Atlas limits the number of nodes per Network Peering connection based on the CIDR block and the region selected for the project.
Pending network peering connections per MongoDB Atlas project
AWS Private Link addressable targets per region
Azure PrivateLink addressable targets per region
Unique shard keys per MongoDB Atlas project
Atlas Data Lake pipelines per MongoDB Atlas project
M0 clusters per MongoDB Atlas project

MongoDB Atlas limits the length and enforces ReGex requirements for the following component labels:

Character Limit
RegEx Pattern
Cluster Name
64 [1]
^([a-zA-Z0-9]([a-zA-Z0-9-]){0,21}(?<!-)([\w]{0,42}))$ [2]
Project Name
^[\p{L}\p{N}\-_.(),:&@+']{1,64}$ [3]
Organization Name
^[\p{L}\p{N}\-_.(),:&@+']{1,64}$ [3]
API Key Description
[1] If you have peering-only mode enabled, the cluster name character limit is 23.
[2] MongoDB Atlas uses the first 23 characters of a cluster's name. These characters must be unique within the cluster's project. Cluster names with fewer than 23 characters can't end with a hyphen (-). Cluster names with more than 23 characters can't have a hyphen as the 23rd character.
[3](1, 2) Organization and project names can include any Unicode letter or number plus the following punctuation: -_.(),:&@+'.

Additional limitations apply to MongoDB Atlas serverless instances, free clusters, and shared clusters. To learn more, see the following resources:

Some MongoDB commands are unsupported in MongoDB Atlas. Additionally, some commands are supported only in MongoDB Atlas free clusters. To learn more, see the following resources:

BSON Document Size

The maximum BSON document size is 16 megabytes.

The maximum document size helps ensure that a single document cannot use excessive amount of RAM or, during transmission, excessive amount of bandwidth. To store documents larger than the maximum size, MongoDB provides the GridFS API. See mongofiles and the documentation for your driver for more information about GridFS.

Nested Depth for BSON Documents

MongoDB supports no more than 100 levels of nesting for BSON documents. Each object or array adds a level.

Use of Case in Database Names

Do not rely on case to distinguish between databases. For example, you cannot use two databases with names like, salesData and SalesData.

After you create a database in MongoDB, you must use consistent capitalization when you refer to it. For example, if you create the salesData database, do not refer to it using alternate capitalization such as salesdata or SalesData.

Restrictions on Database Names for Windows

For MongoDB deployments running on Windows, database names cannot contain any of the following characters:

/\. "$*<>:|?

Also database names cannot contain the null character.

Restrictions on Database Names for Unix and Linux Systems

For MongoDB deployments running on Unix and Linux systems, database names cannot contain any of the following characters:

/\. "$

Also database names cannot contain the null character.

Length of Database Names

Database names cannot be empty and must be less than 64 bytes.

Restriction on Collection Names

Collection names should begin with an underscore or a letter character, and cannot:

  • contain the $.

  • be an empty string (e.g. "").

  • contain the null character.

  • begin with the system. prefix. (Reserved for internal use.)

If your collection name includes special characters, such as the underscore character, or begins with numbers, then to access the collection use the db.getCollection() method in mongosh or a similar method for your driver.

Namespace Length:

The namespace length limit for unsharded collections and views is 255 bytes, and 235 bytes for sharded collections. For a collection or a view, the namespace includes the database name, the dot (.) separator, and the collection/view name (e.g. <database>.<collection>).

Restrictions on Field Names
  • Field names cannot contain the null character.

  • The server permits storage of field names that contain dots (.) and dollar signs ($).

  • MongodB 5.0 adds improved support for the use of ($) and (.) in field names. There are some restrictions. See Field Name Considerations for more details.

Restrictions on _id

The field name _id is reserved for use as a primary key; its value must be unique in the collection, is immutable, and may be of any type other than an array. If the _id contains subfields, the subfield names cannot begin with a ($) symbol.


Use caution, the issues discussed in this section could lead to data loss or corruption.

The MongoDB Query Language does not support documents with duplicate field names. While some BSON builders may support creating a BSON document with duplicate field names, inserting these documents into MongoDB is not supported even if the insert succeeds, or appears to succeed. For example, inserting a BSON document with duplicate field names through a MongoDB driver may result in the driver silently dropping the duplicate values prior to insertion, or may result in an invalid document being inserted that contains duplicate fields. Querying against any such documents would lead to arbitrary and inconsistent results.

Starting in MongoDB 5.0, document field names can be dollar ($) prefixed and can contain periods (.). However, mongoimport and mongoexport may not work as expected in some situations with field names that make use of these characters.

MongoDB Extended JSON v2 cannot differentiate between type wrappers and fields that happen to have the same name as type wrappers. Do not use Extended JSON formats in contexts where the corresponding BSON representations might include dollar ($) prefixed keys. The DBRef mechanism is an exception to this general rule.

There are also restrictions on using mongoimport and mongoexport with periods (.) in field names. Since CSV files use the period (.) to represent data hierarchies, a period (.) in a field name will be misinterpreted as a level of nesting.

There is a small chance of data loss when using dollar ($) prefixed field names or field names that contain periods (.) if these field names are used in conjunction with unacknowledged writes (write concern w=0) on servers that are older than MongoDB 5.0.

When running insert, update, and findAndModify commands, drivers that are 5.0 compatible remove restrictions on using documents with field names that are dollar ($) prefixed or that contain periods (.). These field names generated a client-side error in earlier driver versions.

The restrictions are removed regardless of the server version the driver is connected to. If a 5.0 driver sends a document to an older server, the document will be rejected without sending an error.

Namespace Length

The namespace length limit for unsharded collections and views is 255 bytes, and 235 bytes for sharded collections. For a collection or a view, the namespace includes the database name, the dot (.) separator, and the collection/view name (e.g. <database>.<collection>).


See also:

Number of Indexes per Collection

A single collection can have no more than 64 indexes.

Number of Indexed Fields in a Compound Index

There can be no more than 32 fields in a compound index.

Queries cannot use both text and Geospatial Indexes

You cannot combine the $text query, which requires a special text index, with a query operator that requires a different type of special index. For example you cannot combine $text query with the $near operator.

Fields with 2dsphere Indexes can only hold Geometries

Fields with 2dsphere indexes must hold geometry data in the form of coordinate pairs or GeoJSON data. If you attempt to insert a document with non-geometry data in a 2dsphere indexed field, or build a 2dsphere index on a collection where the indexed field has non-geometry data, the operation will fail.


See also:

The unique indexes limit in Sharding Operational Restrictions.

Limited Number of 2dsphere index keys

To generate keys for a 2dsphere index, mongod maps GeoJSON shapes to an internal representation. The resulting internal representation may be a large array of values.

When mongod generates index keys on a field that holds an array, mongod generates an index key for each array element. For compound indexes, mongod calculates the cartesian product of the sets of keys that are generated for each field. If both sets are large, then calculating the cartesian product could cause the operation to exceed memory limits.

indexMaxNumGeneratedKeysPerDocument limits the maximum number of keys generated for a single document to prevent out of memory errors. The default is 100000 index keys per document. It is possible to raise the limit, but if an operation requires more keys than the indexMaxNumGeneratedKeysPerDocument parameter specifies, the operation will fail.

NaN values returned from Covered Queries by the WiredTiger Storage Engine are always of type double

If the value of a field returned from a query that is covered by an index is NaN, the type of that NaN value is always double.

Multikey Index

Multikey indexes cannot cover queries over array fields.

Geospatial Index

Geospatial indexes can't cover a query.

Memory Usage in Index Builds

createIndexes supports building one or more indexes on a collection. createIndexes uses a combination of memory and temporary files on disk to complete index builds. The default limit on memory usage for createIndexes is 200 megabytes, shared between all indexes built using a single createIndexes command. Once the memory limit is reached, createIndexes uses temporary disk files in a subdirectory named _tmp within the --dbpath directory to complete the build.

You can override the memory limit by setting the maxIndexBuildMemoryUsageMegabytes server parameter. Setting a higher memory limit may result in faster completion of index builds. However, setting this limit too high relative to the unused RAM on your system can result in memory exhaustion and server shutdown.

Index builds may be initiated either by a user command such as createIndexes or by an administrative process such as an initial sync. Both are subject to the limit set by maxIndexBuildMemoryUsageMegabytes.

An initial sync populates only one collection at a time and has no risk of exceeding the memory limit. However, it is possible for a user to start index builds on multiple collections in multiple databases simultaneously and potentially consume an amount of memory greater than the limit set by maxIndexBuildMemoryUsageMegabytes.


To minimize the impact of building an index on replica sets and sharded clusters with replica set shards, use a rolling index build procedure as described on Rolling Index Builds on Replica Sets.

Collation and Index Types

The following index types only support simple binary comparison and do not support collation:


To create a text or 2d index on a collection that has a non-simple collation, you must explicitly specify {collation: {locale: "simple"} } when creating the index.

Hidden Indexes
Maximum Number of Sort Keys

You can sort on a maximum of 32 keys.

Maximum Number of Documents in a Capped Collection

If you specify the maximum number of documents in a capped collection with create's max parameter, the value must be less than 2 31 documents.

If you do not specify a maximum number of documents when creating a capped collection, there is no limit on the number of documents.

Number of Members of a Replica Set

Replica sets can have up to 50 members.

Number of Voting Members of a Replica Set

Replica sets can have up to 7 voting members. For replica sets with more than 7 total members, see Non-Voting Members.

Maximum Size of Auto-Created Oplog

If you do not explicitly specify an oplog size (i.e. with oplogSizeMB or --oplogSize) MongoDB will create an oplog that is no larger than 50 gigabytes. [4]

[4] The oplog can grow past its configured size limit to avoid deleting the majority commit point.

Sharded clusters have the restrictions and thresholds described here.

Operations Unavailable in Sharded Environments

$where does not permit references to the db object from the $where function. This is uncommon in un-sharded collections.

The geoSearch command is not supported in sharded environments.

In MongoDB 5.0 and earlier, you cannot specify sharded collections in the from parameter of $lookup stages.

Covered Queries in Sharded Clusters

When run on mongos, indexes can only cover queries on sharded collections if the index contains the shard key.

Single Document Modification Operations in Sharded Collections

To use update and remove() operations for a sharded collection that specify the justOne or multi: false option:

  • If you only target one shard, you can use a partial shard key in the query specification or,

  • You can provide the shard key or the _id field in the query specification.

Unique Indexes in Sharded Collections

MongoDB does not support unique indexes across shards, except when the unique index contains the full shard key as a prefix of the index. In these situations MongoDB will enforce uniqueness across the full key, not a single field.



Unique Constraints on Arbitrary Fields for an alternate approach.

Maximum Number of Documents Per Range to Migrate

By default, MongoDB cannot move a range if the number of documents in the range is greater than 2 times the result of dividing the configured range size by the average document size. If MongoDB can move a sub-range of a chunk and reduce the size to less than that, the balancer does so by migrating a range. db.collection.stats() includes the avgObjSize field, which represents the average document size in the collection.

For chunks that are too large to migrate:

  • The balancer setting attemptToBalanceJumboChunks allows the balancer to migrate chunks too large to move as long as the chunks are not labeled jumbo. See Balance Ranges that Exceed Size Limit for details.

    When issuing moveRange and moveChunk commands, it's possible to specify the forceJumbo option to allow for the migration of ranges that are too large to move. The ranges may or may not be labeled jumbo.

Shard Key Index Type

A shard key index can be an ascending index on the shard key, a compound index that starts with the shard key and specifies ascending order for the shard key, or a hashed index.

A shard key index cannot be:

Shard Key Selection

Your options for changing a shard key depend on the version of MongoDB that you are running:

Monotonically Increasing Shard Keys Can Limit Insert Throughput

For clusters with high insert volumes, a shard key with monotonically increasing and decreasing keys can affect insert throughput. If your shard key is the _id field, be aware that the default values of the _id fields are ObjectIds which have generally increasing values.

When inserting documents with monotonically increasing shard keys, all inserts belong to the same chunk on a single shard. The system eventually divides the chunk range that receives all write operations and migrates its contents to distribute data more evenly. However, at any moment the cluster directs insert operations only to a single shard, which creates an insert throughput bottleneck.

If the operations on the cluster are predominately read operations and updates, this limitation may not affect the cluster.

To avoid this constraint, use a hashed shard key or select a field that does not increase or decrease monotonically.

Hashed shard keys and hashed indexes store hashes of keys with ascending values.

Sort Operations

If MongoDB cannot use an index or indexes to obtain the sort order, MongoDB must perform a blocking sort operation on the data. The name refers to the requirement that the SORT stage reads all input documents before returning any output documents, blocking the flow of data for that specific query.

If MongoDB requires using more than 100 megabytes of system memory for the blocking sort operation, MongoDB returns an error unless the query specifies cursor.allowDiskUse(). allowDiskUse() allows MongoDB to use temporary files on disk to store data exceeding the 100 megabyte system memory limit while processing a blocking sort operation.

For more information on sorts and index use, see Sort and Index Use.

Aggregation Pipeline Operation

Starting in MongoDB 6.0, the allowDiskUseByDefault parameter controls whether pipeline stages that require more than 100 megabytes of memory to execute write temporary files to disk by default.

  • If allowDiskUseByDefault is set to true, pipeline stages that require more than 100 megabytes of memory to execute write temporary files to disk by default. You can disable writing temporary files to disk for specific find or aggregate commands using the { allowDiskUse: false } option.

  • If allowDiskUseByDefault is set to false, pipeline stages that require more than 100 megabytes of memory to execute raise an error by default. You can enable writing temporary files to disk for specific find or aggregate using the { allowDiskUse: true } option.

The $search aggregation stage is not restricted to 100 megabytes of RAM because it runs in a separate process.

Examples of stages that can write temporary files to disk when allowDiskUse is true are:


Pipeline stages operate on streams of documents with each pipeline stage taking in documents, processing them, and then outputing the resulting documents.

Some stages can't output any documents until they have processed all incoming documents. These pipeline stages must keep their stage output in RAM until all incoming documents are processed. As a result, these pipeline stages may require more space than the 100 MB limit.

If the results of one of your $sort pipeline stages exceed the limit, consider adding a $limit stage.

The profiler log messages and diagnostic log messages includes a usedDisk indicator if any aggregation stage wrote data to temporary files due to memory restrictions.

Aggregation and Read Concern
2d Geospatial queries cannot use the $or operator
Geospatial Queries

Using a 2d index for queries on spherical data can return incorrect results or an error. For example, 2d indexes don't support spherical queries that wrap around the poles.

Geospatial Coordinates
  • Valid longitude values are between -180 and 180, both inclusive.

  • Valid latitude values are between -90 and 90, both inclusive.

Area of GeoJSON Polygons

For $geoIntersects or $geoWithin, if you specify a single-ringed polygon that has an area greater than a single hemisphere, include the custom MongoDB coordinate reference system in the $geometry expression. Otherwise, $geoIntersects or $geoWithin queries for the complementary geometry. For all other GeoJSON polygons with areas greater than a hemisphere, $geoIntersects or $geoWithin queries for the complementary geometry.

Multi-document Transactions

For multi-document transactions:

  • You can create collections and indexes in transactions. For details, see Create Collections and Indexes in a Transaction

  • The collections used in a transaction can be in different databases.


    You cannot create new collections in cross-shard write transactions. For example, if you write to an existing collection in one shard and implicitly create a collection in a different shard, MongoDB cannot perform both operations in the same transaction.

  • You cannot write to capped collections.

  • You cannot use read concern "snapshot" when reading from a capped collection. (Starting in MongoDB 5.0)

  • You cannot read/write to collections in the config, admin, or local databases.

  • You cannot write to system.* collections.

  • You cannot return the supported operation's query plan using explain or similar commands.

  • For cursors created outside of a transaction, you cannot call getMore inside the transaction.

  • For cursors created in a transaction, you cannot call getMore outside the transaction.

The following operations are not allowed in transactions:

Transactions have a lifetime limit as specified by transactionLifetimeLimitSeconds. The default is 60 seconds.

Write Command Batch Limit Size

100,000 writes are allowed in a single batch operation, defined by a single request to the server.

The Bulk() operations in mongosh and comparable methods in the drivers do not have this limit.


A view definition pipeline cannot include the $out or the $merge stage. This restriction also applies to embedded pipelines, such as pipelines used in $lookup or $facet stages.

Views have the following operation restrictions:

Projection Restrictions
$-Prefixed Field Path Restriction
The find() and findAndModify() projection cannot project a field that starts with $ with the exception of the DBRef fields.For example, the following operation is invalid:
db.inventory.find( {}, { "$instock.warehouse": 0, "$item": 0, "detail.$price": 1 } )
$ Positional Operator Placement Restriction
The $ projection operator can only appear at the end of the field path, for example "field.$" or "fieldA.fieldB.$".For example, the following operation is invalid:
db.inventory.find( { }, { "instock.$.qty": 1 } )
To resolve, remove the component of the field path that follows the $ projection operator.
Empty Field Name Projection Restriction
find() and findAndModify() projection cannot include a projection of an empty field name.For example, the following operation is invalid:
db.inventory.find( { }, { "": 0 } )
In previous versions, MongoDB treats the inclusion/exclusion of the empty field as it would the projection of non-existing fields.
Path Collision: Embedded Documents and Its Fields
You cannot project an embedded document with any of the embedded document's fields.For example, consider a collection inventory with documents that contain a size field:
{ ..., size: { h: 10, w: 15.25, uom: "cm" }, ... }
The following operation fails with a Path collision error because it attempts to project both size document and the size.uom field:
db.inventory.find( {}, { size: 1, "size.uom": 1 } )
In previous versions, lattermost projection between the embedded documents and its fields determines the projection:
  • If the projection of the embedded document comes after any and all projections of its fields, MongoDB projects the embedded document. For example, the projection document { "size.uom": 1, size: 1 } produces the same result as the projection document { size: 1 }.

  • If the projection of the embedded document comes before the projection any of its fields, MongoDB projects the specified field or fields. For example, the projection document { "size.uom": 1, size: 1, "size.h": 1 } produces the same result as the projection document { "size.uom": 1, "size.h": 1 }.

Path Collision: $slice of an Array and Embedded Fields
find() and findAndModify() projection cannot contain both a $slice of an array and a field embedded in the array.For example, consider a collection inventory that contains an array field instock:
{ ..., instock: [ { warehouse: "A", qty: 35 }, { warehouse: "B", qty: 15 }, { warehouse: "C", qty: 35 } ], ... }
The following operation fails with a Path collision error:
db.inventory.find( {}, { "instock": { $slice: 1 }, "instock.warehouse": 0 } )
In previous versions, the projection applies both projections and returns the first element ($slice: 1) in the instock array but suppresses the warehouse field in the projected element. Starting in MongoDB 4.4, to achieve the same result, use the db.collection.aggregate() method with two separate $project stages.
$ Positional Operator and $slice Restriction
find() and findAndModify() projection cannot include $slice projection expression as part of a $ projection expression.For example, the following operation is invalid:
db.inventory.find( { "instock.qty": { $gt: 25 } }, { "instock.$": { $slice: 1 } } )
In previous versions, MongoDB returns the first element (instock.$) in the instock array that matches the query condition; i.e. the positional projection "instock.$" takes precedence and the $slice:1 is a no-op. The "instock.$": { $slice: 1 } does not exclude any other document field.
Sessions and $external Username Limit

To use Client Sessions and Causal Consistency Guarantees with $external authentication users (Kerberos, LDAP, or x.509 users), usernames cannot be greater than 10k bytes.

Session Idle Timeout

Sessions that receive no read or write operations for 30 minutes or that are not refreshed using refreshSessions within this threshold are marked as expired and can be closed by the MongoDB server at any time. Closing a session kills any in-progress operations and open cursors associated with the session. This includes cursors configured with noCursorTimeout() or a maxTimeMS() greater than 30 minutes.

Consider an application that issues a db.collection.find(). The server returns a cursor along with a batch of documents defined by the cursor.batchSize() of the find(). The session refreshes each time the application requests a new batch of documents from the server. However, if the application takes longer than 30 minutes to process the current batch of documents, the session is marked as expired and closed. When the application requests the next batch of documents, the server returns an error as the cursor was killed when the session was closed.

For operations that return a cursor, if the cursor may be idle for longer than 30 minutes, issue the operation within an explicit session using Mongo.startSession() and periodically refresh the session using the refreshSessions command. For example:

var session = db.getMongo().startSession()
var sessionId = session
sessionId // show the sessionId
var cursor = session.getDatabase("examples").getCollection("data").find().noCursorTimeout()
var refreshTimestamp = new Date() // take note of time at operation start
while (cursor.hasNext()) {
// Check if more than 5 minutes have passed since the last refresh
if ( (new Date()-refreshTimestamp)/1000 > 300 ) {
print("refreshing session")
db.adminCommand({"refreshSessions" : [sessionId]})
refreshTimestamp = new Date()
// process cursor normally

In the example operation, the db.collection.find() method is associated with an explicit session. The cursor is configured with noCursorTimeout() to prevent the server from closing the cursor if idle. The while loop includes a block that uses refreshSessions to refresh the session every 5 minutes. Since the session will never exceed the 30 minute idle timeout, the cursor can remain open indefinitely.

For MongoDB drivers, defer to the driver documentation for instructions and syntax for creating sessions.


MongoDB Cluster Parameters


MongoDB Package Components