Small overview about LMDB?

Question

What is LMDB?
Lightning Memory-Mapped Database (LMDB) is a software library that provides a high-performance embedded transactional database in the form of a key-value store. LMDB is written in C with API bindings for several programming languages.

LMDB is a Btree-based database management library modeled loosely on the BerkeleyDB API, but much simplified. The entire database is exposed in a memory map, and all data fetches return data directly from the mapped memory, so no malloc's or memcpy's occur during data fetches. As such, the library is extremely simple because it requires no page caching layer of its own, and it is extremely high performance and memory-efficient. It is also fully transactional with full ACID semantics, and when the memory map is read-only, the database integrity cannot be corrupted by stray pointer writes from application code.

The library is fully thread-aware and supports concurrent read/write access from multiple processes and threads. Data pages use a copy-on- write strategy so no active data pages are ever overwritten, which also provides resistance to corruption and eliminates the need of any special recovery procedures after a system crash. Writes are fully serialized; only one write transaction may be active at a time, which guarantees that writers can never deadlock. The database structure is multi-versioned so readers run with no locks; writers cannot block readers, and readers don't block writers.

Unlike other well-known database mechanisms which use either write-ahead transaction logs or append-only data writes, LMDB requires no maintenance during operation. Both write-ahead loggers and append-only databases require periodic checkpointing and/or compaction of their log or database files otherwise they grow without bound. LMDB tracks free pages within the database and re-uses them for new write operations, so the database size does not grow without bound in normal use

Benefits

• LMDB uses memory-mapped files, giving much better I/O performance.
• Works well with really large datasets. The HDF5 files are always read entirely into memory, so you can’t have any HDF5 file exceed your memory capacity. You can easily split your data into several HDF5 files though (just put several paths to h5 files in your text file).​

Video for LMDB?