Architecture independent databases. Scalability Berkeley DB Data Store maintains caches in shared memory. As a result, threads of control in the same process, or in other processes, can share data pages read from disk. Data read by one process is available to others. This improves performance for virtually all database applications.
Applications pay no overhead for locks, and the system never suffers from lock contention.
All of the Berkeley DB products have been carefully designed to support large databases and high concurrency. Berkeley DB can address up to 256 terabytes of data in a single database. Sleepycat Software customers have single databases that are hundreds of gigabytes in size in daily use. Berkeley DB is able to support thousands of threads working on a single database at a time. Growth Path Developers who build on Berkeley DB Data Store have a simple growth path if their applications ever require concurrency or support for transactions and disaster recovery.