Hybrid Database Management System

eXtremeDB makes it easy to combine all the strengths of the on-disk and all-in-memory approaches to data management in a single database system.

This unparalleled flexibility enables developers to tailor data management in order to optimize applications for speed and persistence, while taking advantage of the most cost-effective and physical space-conserving approaches to data storage.

In-memory database systems (IMDSs) such as McObject’s eXtremeDB offer superior performance and the possibility of very small RAM, CPU and storage demands. IMDSs (or RAM databases) boost speed and reduce footprint by eliminating logical and physical disk I/O, multiple data copies, and irrelevant tasks, such as caching. The eXtremeDB In-Memory Database System also includes a transaction logging module to persist in-memory databases. An in-memory database with transaction logging retains the high performance read characteristics and provides tune-able persistence while retaining much of the in-memory database insert/update/delete performance advantage.

In contrast, on-disk databases cache frequently requested data in memory, for faster access, but write database updates, insertions and deletes through the cache to be stored to disk. On the plus side, byte-for-byte, disk storage can be cheaper than RAM, and can also take less physical space.

The best of both worlds: a hybrid database management system.

eXtremeDB enables the developer to easily combine both database paradigms – in-memory and on-disk – in a single database instance. Specifying one set of data as transient (managed in memory), while choosing persistent storage for other record types, requires a simple database schema declaration, as shown below.

transient class classname {
[fields]
};

persistent class classname {
[fields]
};

The resulting embedded database system retains in-memory strengths (speed, small database footprint, intuitive native API, etc.), yet leverages the potential cost savings and increased durability of an on-disk database.