  Although most business application data is stored in relational databases,
programming languages and wire formats in integration middleware systems are
not table-centric. Due to costly format conversions, data-shipments and faster
computation, the trend is to "push-down" the integration operations closer to
the storage representation.
  We address the alternative case of defining declarative, table-centric
integration semantics within standard integration systems. For that, we replace
the current operator implementations for the well-known Enterprise Integration
Patterns by equivalent "in-memory" table processing, and show a practical
realization in a conventional integration system for a non-reliable,
"data-intensive" messaging example. The results of the runtime analysis show
that table-centric processing is promising already in standard, "single-record"
message routing and transformations, and can potentially excel the message
throughput for "multi-record" table messages.
