There are other performance implications that result from the underlying assumption that the in-memory representation of Berkeley DB indices is really a cache for on-disk persistent data. When a test-and-set spin mutex implementation is selected, it may be useful to tune the number of spins made before yielding the processor and sleeping. Get the SourceForge newsletter. For example, whenever Berkeley DB accesses a cached page, it first pins the page in memory. The dbm interfaces to the Berkeley DB library are intended to provide high-performance implementations and source code compatibility for applications written to historic interfaces. Oracle Berkeley DB Java Edition is an open source, embeddable, transactional storage engine written entirely in Java. The software is distributed as a library that can be linked directly into an application. The Berkeley Database (Berkeley DB) is an embedded database system that can be used in applications requiring high-performance concurrent storage and retrieval of key/value pairs. Generally, the speed of a database system is measured by the transaction throughput, expressed as the number of transactions per second.The two gating factors for Berkeley DB performance in a transactional system are usually the underlying database files and the log file. In some cases, better performance can be achieved by configuring with the --with-mutex argument and selecting a different mutex implementation than the one selected by Berkeley DB. Write and Read are concurrent for the db, but write performs best with single thread whereas Read scales with number of cores. Transaction Throughput. It takes full advantage of the Java environment to simplify development and deployment. Berkeley DB offers advanced features including transactional data storage, highly concurrent access, scalability on large SMP systems, replication for high availability, and fault tolerance in a self-contained, small footprint software library. My db type of choice is HASH but I also tried BTREE and it is the same. At the beginning, when the quantity of data was low, the insertion of new rows was fast. I tried using a pool of 10 db's and hashing the docs among them to smooth out the performance drops; this increased the write throughput to 50K docs/s but didn't help with the performance drops: all 10 db's slowed to a crawl at the same time. Get notifications on updates for this project. Slices in Berkeley DB(courtesy of Charles Koester) With the new Berkeley DB 6.2 release, there are a number of new features. BerkleyDB: BerkleyDB (BDB) is a library that provides high performance embedded database for key/value data. 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