LMDB (Lightning Memory-Mapped Database) is a embedded database for key-value data based on B+trees. It is fully ACID transactional. The key features of LMDB are that it uses a single-level store based on memory-map files, which means that the OS is responsible for managing the pages (like caching frequently uses pages). It uses a copy-on-write storage method with a single writer thread; readers do not block writers and writers do not block readers. The system only maintains at most two versions of data at any time (i.e., once committed all the previous versions are discarded). It also maintains a free list of pages to track and reuse pages instead of allocating memory each time.
LMDB was developed and maintained by the Symas Corporation to replace Berkeley DB in the OpenLDAP project.
LMDB has no SQL layer but applications can directly access the database using API calls provided by LMDB. API support is not just in C but many wrappers for other languages have been developed by open-source contributors. All key-value store operations can be performed using these API calls.
Multi-version Concurrency Control (MVCC)
Locking overhead avoided by using MVCC, readers don't block at all and writers don't block readers. Deleted versions are reclaimed by the free space management module of LMDB (essentially stored into a B+ tree for later use).
No logging procedures are implemented here, using copy-on-write semantics (with shadow paging) provides durability without any need for logging. Shadow paging allows new writes to a different location and not directly replace the existing pages, hence avoids data-corruption. Also the shadow page reference update is atomic, hence avoids need for logging.
They use a memory-map to store the database with copy-on-write semantics, hence no specific storage model but the semantics are left to the operating system. The on-disk representation is similar to the memory representation of the database.
LMDB provides Serializable isolation with MVCC, this is possible because of the single-writer semantics. Only a single write transaction can can be alive at a single point of time, hence no races among multiple writers modifying the database.
There is no query planning or query execution options as this is an embedded database, since we operate at individual key level, the closest we can classify it is under tuple-at-a-time. The user can program custom querying models on top this embeddded database, which can support other query execution options.
LMDB uses a modified design of Append-only B+ Tree and it uses 2 B+ trees : one for maintaining the regular user data pages and one for maintaining the free pages obtained after deletes. LMDB is optimized for short read transactions, long lived read transactions will keep older pages longer in the table and hence blocks write operations. If the workload has too many writes along with long lived read transactions, the performance would be very low.
LMDB uses mmap, hence it reliquishes most of the caching control to the OS. Memory map allows zero-copies for read/write and no additional buffers for the transaction control. Supports larger-than memory databases, it is bounded by the size of the virtual memory since they use a memory map.
This embedded database is a key-value in the backend, which is stored in the memory-map. The keys are indexed in a B+ tree. LMDB provides transactional guarantees on top of this key-value store. It is not a relational database.
LMDB uses shared-memory model i.e. it handles the memory as a single address space and all the threads access this in parallel. It uses copy-on-write semantics.
AIX, Android, BSD, iOS, Linux, OS X, Solaris, Windows