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Whitepaper
Request: A Comparison and Mapping of Data Distribution Service (DDS) and
Java Message Service (JMS)
Abstract:
Data-centric design is emerging as a key tenet for building advanced data-critical distributed embedded and enterprise systems. DDS and JMS are popular middleware API standards that are easy to use, and offer the benefits of using a publish-subscribe communication model resulting in loosely coupled scalable distributed applications. However, their differences have significant impact on a data-centric design.
DDS and JMS are based on fundamentally different paradigms with respect to data modeling, dataflow routing, discovery, and data typing; yet they offer a similar and easy to use experience to the application programmer. They differ significantly in their support for data filtering and transformation, connectivity monitoring, redundancy and replication, and delivery effort. Each also offers some distinct capabilities; and they both offer some equivalent capabilities. We provide a detailed functional comparison of the two standards, and discuss their implications on datacentric design.
We also discuss the practical considerations and differences in using the two standards. These include middleware architecture, platform support, interoperability, transports, security, administration, performance, scalability, real-time application specific support, and enterprise application specific support.
DDS and JMS APIs may be used together in an application. The can leverage each other via JMS-DDS bridging, JMS/DDS bindings, or by using DDS for JMS discovery. We discuss these approaches and their suitability for different data-centric integration scenarios.
DDS and JMS merit careful consideration for data-centric design and integration. Using one or both can considerably simplify data-centric development, and help maintain the focus on application issues, rather than becoming hijacked by communication and data delivery concerns.
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