RDM Embedded

RDM Embedded is a high-performance, embedded database management system, designed to meet today’s complex interconnected applications and devices. The core database engine is implemented as a linkable library, allowing it to become an embedded part of C/C++ applications. It has been designed to utilize multi-core computers, networking (local or wide area) and in-memory or on-disk storage. The product also provides a low-level C API and higher level C++ or SQL APIs, and supports the network and relational data models.

RDM Embedded 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 embedded operating systems many of which have limited computing resources.

The ACID compliant engine allows for mirroring, replication and distributed environments. It supports B-tree and hash indexes; the B-tree indices can support simple and/or compound keys. This core engine can be ported to all the main real-time or embedded operating systems. With a nearly 30 years of development history, it is estimated that this embedded database management system has been used by more than 20,000 developers and deployed in over 20 million installations in all the major industries; including Aerospace & Defense, Automotive, Business Automation, Financial, Government, Industrial Automation, Medical, and Telecommunication.

Performance Driven Features

  • Multi-Core Support

    Efficiently allocate transaction processing to take advantage of multi-core systems for optimal speed.

  • Multi-Versioning Concurrency Control (MVCC)

    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.

  • Pure and Hybrid In-Memory Database Operation

    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.

  • Multiple Indexing Methods

    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.