Tiny Footprint Data Management System
Small, fast, reliable eXtremeDB was designed for needs of embedded systems.
eXtremeDB’s streamlined design minimizes embedded system’s demand for memory and CPU resources.
eXtremeDB’s small code size is approximately 250K, and this footprint can be reduced to as little as 150K when features (such as support for floating point, events) are selectively compiled out using eXtremeDB’s available source code. Elimination of disk I/O and caching logic significantly reduce CPU demands.
Why does a small footprint matter?
Nearly every developer likes to be able to get more performance from available CPU and memory. And in some categories, eXtremeDB’s frugality in resource consumption provides a critical competitive advantage.
For example, in consumer electronics, using less expensive memory and CPU components, eXtremeDB lowers a device’s bill-of-materials costs. This enables a manufacturer to set a more competitive price point — or to drop the savings directly to the bottom line.
With an embedded database that demands less memory and CPU cycles, these resources can be used to develop more and better features for the end user. CPU hits consume power, too, so using an embedded database with minimal CPU demands contributes to longer battery life in devices such as portable audio players.
JVC, the Japanese consumer electronics giant, integrated eXtremeDB in its portable audio player, to take advantage of the benefits described above. To learn more about their project, read the article, “How to manage playlist data in MP3 player embedded software“.
Get more information about eXtremeDB for the IoT. Learn how powerful a database management system with small code size can be, and try platform-independent eXtremeDB.
Review the white paper, “Exploring Code Size and Footprint”
Learn more about eXtremeDB in hard real-time systems
Tiny footprint eXtremeDB is found in over 30,000,000 deployments world-wide in these and other markets
What do you need most from a database management system?
Review the extensive list of features.
Related Resources
Exploring Code Size and Footprint, and In-Memory Database Techniques to Minimize Footprint
A white paper from the in-memory database management system experts at McObject. The terms ‘code size’ and ‘footprint’ are often used interchangeably. But they are not the same; code size is a subset of footprint. This paper will explain the differentiation and relevance, then proceed to describe some of the techniques employed within eXtremeDB to minimize footprint.
Using Data Indexes to Boost Performance and Minimize Footprint in Embedded Software
This Webinar examines less well-known indexes including T-Tree, Hash table, R-Tree, Patricia trie and others. It emphasizes index implementation methods that avoid data duplication, to minimize an memory footprint.
Kernel Mode Database Systems for Real-Time Applications
With a small footprint, embedded all-in-memory database system, it is possible to integrate a very low-overhead, yet full-featured, database engine in the operating system kernel. Watch the Webinar to learn more.
Used by innovative industry leaders in over 30,000,000 deployments world-wide in these markets and others.
Network & Telecom
Network gear developers build on proven eXtremeDB speed and reliability, combined in-memory and persistent data layouts, optimized access methods and unmatched flexibility.
Consumer electronics
eXtremeDB’s small code size (approximately 200K) reduces device hardware costs, while its unmatched speed delivers a better user experience.
Industrial Systems
eXtremeDB’s sophisticated event notification systems, time series data processing and high availability have powered its wide-spread adoption in SCADA, fleet management, smart building automation and other verticals.
Aerospace & Defense
Northrop Grumman, Lockheed Martin, British Aerospace, EADS and others depend on eXtremeDB’s reliability, unmatched performance and broad platform support.
Energy
eXtremeDB optimization technology can dramatically boost utilities’ power generation yields. Distribution networks can become self-healing and bi-directional, enabling end-users to contribute power back to the grid.
Finance
eXtremeDB’s unique hybrid row- and columnar-layout (OLTP and time series) couples with pipelined functions for statistical analysis and scalable distributed database architecture power record-setting STAC-M3 benchmark results.