The versatile server and desktop database.
Server and Desktop Database Overview
RDM Workgroup Edition is a high-performance, database management system optimized for the operating systems commonly used within the desktop and server environments.
It is ideal for standalone and networked applications such as those commonly found on today’s desktop and laptop computers. Multiple APIs provide developers a multitude of programming options and functionality.
In addition RDM Workgroup includes an ADO.Net 4.0 provider, JDBC 4 Type 4 driver and an ODBC 3.5 driver. Using these drivers managed code applications can easily be created using popular languages like C# and Java.
The ACID compliant desktop database engine supports B-tree and hash indexes; the B-tree indices can support simple and/or compound keys. Additionally the desktop 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 desktop 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 desktop 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.
Easily achieve true horizontal scaling across clustered or distributed systems without the need to re-write of your application.
Connect any application to one or more databases and query them as if it is a single instance. Perform global, locally or across a network, to multiple database instances with no regard for where the data is located.