When architecting next-generation central compute clusters, Tier-1 automotive software teams face a critical choice: wrap services inside the heavyweight AUTOSAR Adaptive Platform (ara::com) or deploy direct native OMG DDS middleware. This article benchmarks memory footprints, serialization latency, and ISO 26262 ASIL-D certification complexity across both paradigms.
While native OMG DDS implementations (like eProsima Fast DDS or RTI Connext) compile into compact shared libraries requiring less than 4MB of RAM per process, standard AUTOSAR Adaptive stacks require comprehensive daemon infrastructure (Execution Manager, State Manager, DLT logging daemons) consuming over 45MB of baseline RAM before the first application launches.
Where AUTOSAR Adaptive excels is functional safety certification. Commercial Adaptive offerings (e.g. Vector MICROSAR, Elektrobit Corbos) provide turnkey ISO 26262 ASIL-D safety manuals and pre-validated diagnostic hooks. Native DDS solutions require system architects to manually compose and certify safety cases for dynamic memory allocation and communication channels.