Oracle has a big problem: When its customers purchase more memory, they expect performance to improve. Yet bigger caches require more CPU cycles to manage, and Oracle's algorithms, which were developed with the expectation of more IO and less memory, become stressed in ways they were not originally intended to handle. The result can be bizarre and deep contention related to memory structure.

Oracle TimesTen In-Memory Database delivers real-time performance by changing the assumptions around where data resides at runtime. By managing data in memory, and optimizing data structures and access algorithms accordingly, database operations execute with maximum efficiency, achieving dramatic gains in responsiveness and throughput, even compared to a fully cached disk-based RDBMS.1

Right away, Oracle states the assumption has changed. The assumption is the data resides in memory. In contrast to the standard Oracle kernel, where a balance must be struck between disk IO and in-memory operations, the TimesTen database is specifically designed for in-memory operations. It even goes so far as to say that an in-memory Oracle database cannot match the TimesTen performance! Clearly, trade-offs have been made to break speed barriers in specific processing areas.