Benchmarking MongoDB's GridFS vs PostgreSQL's LargeObjects.

gridfs-vs-lobjects.py

import io
import pymongo
import psycopg2
import gridfs
import timeit

# For fairness use the same chunk size - 512k.
CHUNK_SIZE = 1024 * 512

def bench_mongo(fs, size):
    fp = io.BytesIO('x'*size)
    fp.seek(0)
    fs.put(fp, chunk_size=CHUNK_SIZE)

def bench_pg(conn, size):
    fp = io.BytesIO('x'*size)
    fp.seek(0)
    lob = conn.lobject(mode='wb')
    while 1:
        chunk = fp.read(CHUNK_SIZE)
        if not chunk:
            break
        lob.write(chunk)
    conn.commit()

mongo = pymongo.MongoClient()

for name, size, reps in (('1k', 1024, 10000), ('10k', 10240, 10000), ('1M', 1024*1024, 1000), ('10M', 1024*1024*10, 100)):
    fs = gridfs.GridFS(mongo.lobs_test_database)
    t = timeit.timeit('bench_mongo(fs, %s)' % size, 'from __main__ import bench_mongo, fs', number=reps)
    print "mongo: %3s x %5s: %0.2fs (%0.4fs/op)" % (name, reps, t, t/reps)
    mongo.drop_database('lobs_test_database')

    conn = psycopg2.connect(dbname='template1')
    conn.autocommit = True
    conn.cursor().execute('CREATE DATABASE lobs_test_database')
    conn.close()
    conn = psycopg2.connect(dbname='lobs_test_database')
    t = timeit.timeit('bench_pg(conn, %s)' % size, 'from __main__ import bench_pg, conn', number=reps)
    print "pgsql: %3s x %5s: %0.2fs (%0.4fs/op)" % (name, reps, t, t/reps)
    conn.close()
    conn = psycopg2.connect(dbname='template1')
    conn.autocommit = True
    conn.cursor().execute('DROP DATABASE lobs_test_database')
    conn.close()

See updated version at https://gist.github.com/5005548, with better stats and results.