Bulk Write Operations


MongoDB provides clients the ability to perform write operations in bulk. Bulk write operations affect a single collection. MongoDB allows applications to determine the acceptable level of acknowledgement required for bulk write operations.

New in version 3.2.

The db.collection.bulkWrite() method provides the ability to perform bulk insert, update, and remove operations. MongoDB also supports bulk insert through the db.collection.insertMany().

Ordered vs Unordered Operations

Bulk write operations can be either ordered or unordered.

With an ordered list of operations, MongoDB executes the operations serially. If an error occurs during the processing of one of the write operations, MongoDB will return without processing any remaining write operations in the list. See ordered Bulk Write

With an unordered list of operations, MongoDB can execute the operations in parallel, but this behavior is not guaranteed. If an error occurs during the processing of one of the write operations, MongoDB will continue to process remaining write operations in the list. See Unordered Bulk Write.

Executing an ordered list of operations on a sharded collection will generally be slower than executing an unordered list since with an ordered list, each operation must wait for the previous operation to finish.

By default, bulkWrite() performs ordered operations. To specify unordered write operations, set ordered : false in the options document.

See Execution of Operations

bulkWrite() Methods

bulkWrite() supports the following write operations:

Each write operation is passed to bulkWrite() as a document in an array.

For example, the following performs multiple write operations:

The characters collection contains the following documents:

{ "_id" : 1, "char" : "Brisbane", "class" : "monk", "lvl" : 4 },
{ "_id" : 2, "char" : "Eldon", "class" : "alchemist", "lvl" : 3 },
{ "_id" : 3, "char" : "Meldane", "class" : "ranger", "lvl" : 3 }

The following bulkWrite() performs multiple operations on the collection:

try {
         { insertOne :
               "document" :
                  "_id" : 4, "char" : "Dithras", "class" : "barbarian", "lvl" : 4
         { insertOne :
               "document" :
                  "_id" : 5, "char" : "Taeln", "class" : "fighter", "lvl" : 3
         { updateOne :
               "filter" : { "char" : "Eldon" },
               "update" : { $set : { "status" : "Critical Injury" } }
         { deleteOne :
            { "filter" : { "char" : "Brisbane"} }
         { replaceOne :
               "filter" : { "char" : "Meldane" },
               "replacement" : { "char" : "Tanys", "class" : "oracle", "lvl" : 4 }
catch (e) {

The operation returns the following:

   "acknowledged" : true,
   "deletedCount" : 1,
   "insertedCount" : 2,
   "matchedCount" : 2,
   "upsertedCount" : 0,
   "insertedIds" : {
      "0" : 4,
      "1" : 5
   "upsertedIds" : {


For more examples, see bulkWrite() Examples

Strategies for Bulk Inserts to a Sharded Collection

Large bulk insert operations, including initial data inserts or routine data import, can affect sharded cluster performance. For bulk inserts, consider the following strategies:

Pre-Split the Collection

If the sharded collection is empty, then the collection has only one initial chunk, which resides on a single shard. MongoDB must then take time to receive data, create splits, and distribute the split chunks to the available shards. To avoid this performance cost, you can pre-split the collection, as described in Split Chunks in a Sharded Cluster.

Unordered Writes to mongos

To improve write performance to sharded clusters, use bulkWrite() with the optional parameter ordered set to false. mongos can attempt to send the writes to multiple shards simultaneously. For empty collections, first pre-split the collection as described in Split Chunks in a Sharded Cluster.

Avoid Monotonic Throttling

If your shard key increases monotonically during an insert, then all inserted data goes to the last chunk in the collection, which will always end up on a single shard. Therefore, the insert capacity of the cluster will never exceed the insert capacity of that single shard.

If your insert volume is larger than what a single shard can process, and if you cannot avoid a monotonically increasing shard key, then consider the following modifications to your application:

  • Reverse the binary bits of the shard key. This preserves the information and avoids correlating insertion order with increasing sequence of values.
  • Swap the first and last 16-bit words to “shuffle” the inserts.


The following example, in C++, swaps the leading and trailing 16-bit word of BSON ObjectIds generated so they are no longer monotonically increasing.

using namespace mongo;
OID make_an_id() {
  OID x = OID::gen();
  const unsigned char *p = x.getData();
  swap( (unsigned short&) p[0], (unsigned short&) p[10] );
  return x;

void foo() {
  // create an object
  BSONObj o = BSON( "_id" << make_an_id() << "x" << 3 << "name" << "jane" );
  // now we may insert o into a sharded collection

See also

Shard Keys for information on choosing a sharded key. Also see Shard Key Internals (in particular, Choosing a Shard Key).