lmdbm

This is a Python DBM interface style wrapper around LMDB (Lightning Memory-Mapped Database). It uses the existing lower level Python bindings py-lmdb. This is especially useful on Windows, where otherwise dbm.dumb is the default dbm database.

Install

• pip install lmdbm

Example

from lmdbm import Lmdb
with Lmdb.open("test.db", "c") as db:
  db[b"key"] = b"value"
  db.update({b"key1": b"value1", b"key2": b"value2"})  # batch insert, uses a single transaction

Use inheritance to store Python objects using json serialization

import json
from lmdbm import Lmdb

class JsonLmdb(Lmdb):
  def _pre_key(self, value):
    return value.encode("utf-8")
  def _post_key(self, value):
    return value.decode("utf-8")
  def _pre_value(self, value):
    return json.dumps(value).encode("utf-8")
  def _post_value(self, value):
    return json.loads(value.decode("utf-8"))

with JsonLmdb.open("test.db", "c") as db:
  db["key"] = {"some": "object"}
  obj = db["key"]
  print(obj["some"])  # prints "object"

Warning

As of lmdb==1.2.1 the docs say that calling lmdb.Environment.set_mapsize from multiple processes "may cause catastrophic loss of data". If lmdbm is used in write mode from multiple processes, set autogrow=False and map_size to a large enough value: Lmdb.open(..., map_size=2**30, autogrow=False).

Benchmarks

Install lmdbm[bench] and run benchmark.py. Other storage engines which could be tested: wiredtiger, berkeleydb.

Storage engines not benchmarked:

• tinydb (because it doesn't have built-in str/bytes keys)

continuous writes in seconds (best of 3)

items	lmdbm	lmdbm-batch	pysos	sqlitedict	sqlitedict-batch	dbm.dumb	semidbm	vedis	vedis-batch	unqlite	unqlite-batch
10	0.000	0.015	0.000	0.031	0.000	0.016	0.000	0.000	0.000	0.000	0.000
100	0.094	0.000	0.000	0.265	0.016	0.188	0.000	0.000	0.000	0.000	0.000
1000	1.684	0.016	0.015	3.885	0.124	2.387	0.016	0.015	0.015	0.016	0.000
10000	16.895	0.093	0.265	45.334	1.326	25.350	0.156	0.093	0.094	0.094	0.093
100000	227.106	1.030	2.698	461.638	12.964	238.400	1.623	1.388	1.467	1.466	1.357
1000000	3482.520	13.104	27.815	5851.239	133.396	2432.945	16.411	15.693	15.709	14.508	14.103

random reads in seconds (best of 3)

items	lmdbm	lmdbm-batch	pysos	sqlitedict	sqlitedict-batch	dbm.dumb	semidbm	vedis	vedis-batch	unqlite	unqlite-batch
10	0.000		0.000	0.000		0.000	0.000	0.000		0.000
100	0.000		0.000	0.031		0.000	0.000	0.000		0.000
1000	0.016		0.015	0.250		0.109	0.016	0.015		0.000
10000	0.109		0.156	2.558		1.123	0.171	0.109		0.109
100000	1.014		2.137	27.769		11.419	2.090	1.170		1.170
1000000	10.390		24.258	447.613		870.580	22.838	214.486		211.319