The efficient embedded database for embedded systems and applications
Embedded Database Overview
RDM Embedded Edition is a high-performance, embedded database management system optimized for the operating systems commonly used within the embedded market.
It is ideal for standalone applications such as those found in industrial automation controllers or automobile infotainment systems. Multiple APIs provide developers with a multitude of programming options and functionality. However, developers can only compile in what they need in order to keep the application footprint minimal for these traditionally resource constrained devices.
RDM Embedded’s SQL has been designed for embedded systems applications. As such, it provides a subset of the ANSI/ISO standard SQL that is suitable for running on a wide variety of computers and operating systems, many of which have limited computing capabilities.
The ACID compliant database engine supports B-tree and hash indexes; the B-tree indices can support simple and/or compound keys. Additionally the embedded database engine has been developed to fully utilize multi-core processors, run within minimal memory, and support both in-memory and on-disk storage. Implemented as a linkable library the database is allowed to become an embedded part of your applications.
The Plus package includes extra features for optimal performance.
New Feature: Performance Benchmarks and Database Functionality Tutorials
Our Database Performance Popcorn Samples let you test in-memory, on-disk performance and other configurations within your app’s environment. You can also view quick database tutorials that show you how to configure different features within our database. Each sample takes less than 5 minutes.
Performance Driven Features
Efficiently allocate transaction processing to take advantage of multi-core systems for optimal speed.
Implement read-only-transactions where a virtual snapshot of your embedded database is readable until the read-only-transaction is terminated by the task, even if it is being concurrently updated. Avoid read locks to improve multi-user performance.
Configure your database to run completely on-disk, completely in-memory, or a hybrid of both; combining the speed of an in-memory database and the stability of on-disk in a single system.
Use B-Trees or Hash Indexes on tables. Hashing on large volumes often provides faster access to data than b-tree indexing methods. Hashing enhances speed by using buckets to store the index information.