Some mongoengine vs pymongo timing comparisons based on https://gist.github.com/BeardedSteve/a1484adcf7475f62028e/ and discussion at http://stackoverflow.com/questions/35257305/mongoengine-is-very-slow-on-large-documents-comapred-to-native-pymongo-usage Example using Embeded documents, with additional comparison against Marrow Mongo and PyModm.

35257305_better_v2.py

import datetime
import itertools
import random
import sys
import timeit
from collections import defaultdict
from pymongo import version as pymongo_version
from distutils.version import StrictVersion
import mongoengine as db
from pycallgraph.output.graphviz import GraphvizOutput
from pycallgraph.pycallgraph import PyCallGraph

db.connect("test-dicts")


class Data(db.EmbeddedDocument):
    subf0 = db.ListField(db.IntField())
    subf1 = db.ListField(db.IntField())
    subf2 = db.ListField(db.IntField())
    subf3 = db.ListField(db.IntField())
    subf4 = db.ListField(db.IntField())


class MyDictModel(db.Document):
    date = db.DateTimeField(required=True, default=datetime.date.today)
    data_dict_1 = db.DictField()


class MyEmbedModel(db.Document):
    date = db.DateTimeField(required=True, default=datetime.date.today)
    data_dict_1 = db.EmbeddedDocumentField(Data)


MyDictModel.drop_collection()
MyEmbedModel.drop_collection()

data = ["subf{}".format(f) for f in range(5)]

m_dict = MyDictModel()
my_dict = dict([(d, list(random.sample(range(50000), 20000))) for d in data])
m_dict.data_dict_1 = my_dict
m_dict.save()

m_embed = MyEmbedModel()
my_data = Data()
for f in data:
    my_data[f] = list(random.sample(range(50000), 20000))
m_embed.data_dict_1 = my_data
m_embed.save()


def pymongo_dict_doc():
    r = db.connection.get_connection()["test-dicts"]['my_dict_model'].find_one()
    print((type(r), len(r)))
    return r

def pymongo_embed_doc():
    r = db.connection.get_connection()["test-dicts"]['my_embed_model'].find_one()
    print((type(r), len(r)))
    return r

def mongoengine_dict_doc():
    r = MyDictModel.objects.first()
    print((type(r.data_dict_1), len(r.data_dict_1)))
    return r

def mongoengine_embed_doc():
    r = MyEmbedModel.objects.first()
    print((type(r.data_dict_1), len(r.data_dict_1)))
    return r

def mongoengine_dict_docp():
    r = MyDictModel.objects.as_pymongo().first()
    print((type(r), len(r)))
    return r

def mongoengine_embed_docp():
    r = MyEmbedModel.objects.as_pymongo().first()
    print((type(r), len(r)))
    return r

def mongoengine_agg_doc():
    r = list(MyDictModel.objects.aggregate({"$limit":1}))[0]    
    print((type(r), len(r)))
    return r

def mongoengine_agg_embed():
    r = list(MyEmbedModel.objects.aggregate({"$limit":1}))[0]    
    print((type(r), len(r)))
    return r
    #return

if __name__ == '__main__':
    print("pymongo with dict took {:2.2f}s".format(timeit.timeit(pymongo_dict_doc, number=10)))
    print("pymongo with embed took {:2.2f}s".format(timeit.timeit(pymongo_embed_doc, number=10)))
    print("mongoengine with dict took {:2.2f}s".format(timeit.timeit(mongoengine_dict_doc, number=10)))
    print("mongoengine with embed took {:2.2f}s".format( timeit.timeit(mongoengine_embed_doc, number=10)))
    print("mongoengine with dict as_pymongo() took {:2.2f}s".format(timeit.timeit(mongoengine_dict_docp, number=10)))
    print("mongoengine with embed  as_pymongo()  took {:2.2f}s".format( timeit.timeit(mongoengine_embed_docp, number=10)))
    if StrictVersion(pymongo_version) < StrictVersion('3.0.0'):
        print("Skipping aggregation on pymongo < 3.x")
    else:
        print("mongoengine aggregation with dict took {:2.2f}s".format( timeit.timeit(mongoengine_agg_doc, number=10)))
        print("mongoengine aggregation with embed took {:2.2f}s".format( timeit.timeit(mongoengine_agg_embed, number=10)))
    out1 = GraphvizOutput()
    out1.output_file = "viz_embed.png"
    out2 = GraphvizOutput()
    out2.output_file = "viz_dict.png"
    with PyCallGraph(output=out1):
        mongoengine_embed_doc()
    with PyCallGraph(output=out2):
        mongoengine_dict_doc()