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This is a guest post by Sachin Sinha, Founder of Iqlect and developer of BangDB.
The goal for the paper is to provide the performances data for following embedded databases under various scenarios for random operations such as write and read. The data is presented in graphical manner to make the data self explanatory to some extent.
- LevelDB:
LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values. Leveldb is based on LSM (Log-Structured Merge-Tree) and uses SSTable and MemTable for the database implementation. It's written in C++ and availabe under BSD license. LevelDB treats key and value as arbitrary byte arrays and stores keys in ordered fashion. It uses snappy compression for the data compression. Write and Read are concurrent for the db, but write performs best with single thread whereas Read scales with number of cores
- BerkleyDB:
BerkleyDB (BDB) is a library that provides high performance embedded database for key/value data. Its the most widely used database library with millions of deployed copies. BDB can be configured to run from concurrent data store to transactional data store to fully ACID compliant db. It's written in C and availabe under Sleepycat Public License. BDB treats key and value as arbitrary byte arrays and stores keys in both ordered fashion using BTREE and un-ordered way using HASH. Write and Read are concurrent for the db, and scales well with number of cores especially the Read operation
- BangDB:
BangDB is a high performance embedded database for key value data. It's a new entrant into the embedded db space. It's written in C++ and available under BSD license. BangDB treats key and value as arbitrary byte arrays and stores keys in both ordered fashion using BTREE and un-ordered way using HASH. Write, Read are concurrent and scales well with the number of cores
The comparison has been done on the similar grounds (as much as possible) for all the dbs to measure the data as crisply and accurately as possible.
The results of the test show BangDB faster in both reads and writes:
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