Reliable and efficient key--value database for Linux?

pts picture pts · Nov 6, 2009 · Viewed 8.2k times · Source

I need a fast, reliable and memory-efficient key--value database for Linux. My keys are about 128 bytes, and the maximum value size can be 128K or 256K. The database subsystem shouldn't use more than about 1 MB of RAM. The total database size is 20G (!), but only a small random fraction of the data is accessed at a time. If necessary, I can move some data blobs out of the database (to regular files), so the size gets down to 2 GB maximum. The database must survive a system crash without any loss in recently unmodified data. I'll have about 100 times more reads than writes. It is a plus if it can use a block device (without a filesystem) as storage. I don't need client-server functionality, just a library. I need Python bindings (but I can implement them if they are not available).

Which solutions should I consider, and which one do you recommend?

Candidates I know of which could work:

  • Tokyo Cabinet (Python bindings are pytc, see also pytc example code, supports hashes and B+trees, transaction log files and more, the size of the bucket array is fixed at database creation time; the writer must close the file to give others a chance; lots of small writes with reopening the file for each of them are very slow; the Tyrant server can help with the lots of small writes; speed comparison between Tokyo Cabinet, Tokyo Tyrant and Berkeley DB)
  • VSDB (safe even on NFS, without locking; what about barriers?; updates are very slow, but not as slow as in cdb; last version in 2003)
  • BerkeleyDB (provides crash recovery; provides transactions; the bsddb Python module provides bindings)
  • Samba's TDB (with transactions and Python bindings, some users experienced corruption, sometimes mmap()s the whole file, the repack operation sometimes doubles the file size, produces mysterious failures if the database is larger than 2G (even on 64-bit systems), cluster implementation (CTDB) also available; file grows too large after lots of modifications; file becomes too slow after lots of hash contention; no built-in way to rebuild the file; very fast parallel updates by locking individual hash buckets)
  • aodbm (append-only so survives a system crash, with Python bindings)
  • hamsterdb (with Python bindings)
  • C-tree (mature, versatile commercial solution with high performance, has a free edition with reduced functionality)
  • the old TDB (from 2001)
  • bitcask (log-structured, written in Erlang)
  • various other DBM implementations (such as GDBM, NDBM, QDBM,, Perl's SDBM or Ruby's; probably they don't have proper crash recovery)

I won't use these:

  • MemcacheDB (client-server, uses BereleleyDB as a backend)
  • cdb (needs to regenerate the whole database upon each write)
  • http://www.wildsparx.com/apbcdb/ (ditto)
  • Redis (keeps the whole database in memory)
  • SQLite (it becomes very slow without periodic vacuuming, see autocompletion in the in the location bar in Firefox 3.0, even though versions 3.1 and later of sqlite allow auto_vacuuming; beware: small writing transactions can be very slow; beware: if a busy process is doing many transactions, other processes starve, and they can never get the lock)
  • MongoDB (too heavy-weight, treats values as objects with internal structure)
  • Firebird (SQL-based RDBMS, too heavy-weight)

FYI, a recent article about key--value databases in the Linux magazine.

FYI, an older software list

FYI, a speed comparison of MemcacheDB, Redis and Tokyo Cabinet Tyrant

Related questions on StackOverflow:

Answer

hyc picture hyc · Aug 4, 2014

LMDB is the most memory-efficient database around http://symas.com/mdb/inmem/

and also proven to be the most reliable - completely crash-proof. http://wisdom.cs.wisc.edu/workshops/spring-14/talks/Thanu.pdf

Of the ones you've mentioned, Tokyo Cabinet has documented corruption issues https://www.google.com/search?q=cfengine+tokyo+cabinet+corruption

BerkeleyDB also has well-documented corruption issues, as does Bitcask. (And bitcask is an in-memory-only DB anyway, so useless for your 1MB RAM requirement.)

LMDB is also well-supported in Python, with a couple different bindings available. https://github.com/dw/py-lmdb/ https://github.com/tspurway/pymdb-lightning

Disclaimer - I am the author of LMDB. But these are documented facts: LMDB is the smallest, most efficient, and most reliable key/value store in the world and nothing else comes anywhere close.