1. Introduction
  2. Overview for the Oracle TimesTen In-Memory Database
  3. TimesTen Database Performance Overview

TimesTen Database Performance Overview

Much of the work that is done by a conventional RDBMS is done under the assumption that data primarily resides on the file system. Optimization algorithms, buffer pool management, and indexed retrieval techniques are designed based on this fundamental assumption.

Even when a file system-based RDBMS has been configured to hold all of its data in main memory, its performance is limited by assumptions of the data residency. These assumptions cannot be easily reversed because they are hard-coded in processing logic, indexing schemes, and data access mechanisms.

Because the TimesTen database resides in physical memory, access to data is more direct, resulting in a shorter code path, simpler algorithms, and internal data structures. Thus, TimesTen delivers performance by optimizing data residency at run time. By managing data in physical memory and optimizing data structures and access algorithms accordingly, database operations run with maximum efficiency, achieving dramatic gains in responsiveness and throughput.

When the assumption of the file system is removed, complexity is dramatically reduced. The number of machine instructions drops, buffer pool management disappears, extra data copies are not needed, index pages shrink, and their structure is simplified. The design becomes simple and more compact, and requests are processed faster. Figure 1-1 shows the simplicity of the TimesTen design.

Figure 1-1 Comparing a File System-Based RDBMS to TimesTen Classic

Description of Figure 1-1 follows
Description of "Figure 1-1 Comparing a File System-Based RDBMS to TimesTen Classic"

Both TimesTen Scaleout and TimesTen Classic deliver high performance since they all use the Oracle TimesTen In-Memory Database as their RDBMS. TimesTen Scaleout provides the best throughput; TimesTen Classic provides the best latency. The TimesTen in-memory database delivers high performance by changing the assumptions about where data resides at runtime. The TimesTen in-memory database manages data in memory and optimizes data structures and access algorithms accordingly. Thus, database operations run with maximum efficiency, achieving dramatic gains in responsiveness and throughput, even compared with a fully cached, the file system-based relational database management system (RDBMS).