Data-centric integration modeling

1. A computer-implemented method comprising:

receiving, by operation of an integration system, a logic integration program comprising a plurality of logic integration patterns that are defined in a data-centric logic integration language;

generating a logical model graph based on the logic integration program, the logical model graph being runtime-independent;

bi-directionally converting the logical model graph into a physical model graph, the physical model graph being runtime-specific, wherein converting the logical model graph into a physical model graph comprises:

detecting logic integration patterns of the logical model graph as detected logic integration patterns; and

synthesizing one or more message channels based on the detected logic integration patterns; and

generating logic integration runtime codes executable by the integration system based on the physical model graph.

2. The method of claim 1 , further comprising defining the logic integration program using the data-centric logic integration language for declarative integration programming.

3. The method of claim 2 , wherein defining a logic integration program comprises:

analyzing integration logic represented by the logical model graph; and

adding integration artifacts.

4. The method of claim 1 , wherein the logical model graph comprises one or more annotations defined by the data-centric logic integration language as one or more nodes of the logical model graph.

5. The method of claim 1 , wherein the logical model graph comprises no cycles.

6. The method of claim 1 , wherein converting the logical model graph into the physical model graph comprises:

detecting patterns on the logical model graph; and

performing a rule-based transformation of the patterns on the logical model graph; and mapping into implementation-specific messaging channels.

7. The method of claim 6 , further comprising optimizing the logical model graph.

8. A non-transitory, computer-readable medium storing computer-readable instructions executable by a computer and configured to:

receive a logic integration program comprising a plurality of logic integration patterns that are defined in a data-centric logic integration language;

generate a logical model graph based on the logic integration program, the logical model graph being runtime-independent;

bi-directionally convert the logical model graph into a physical model graph, the physical model graph being runtime-specific, wherein converting the logical model graph into a physical model graph comprises:

detect logic integration patterns of the logical model graph as detected logic integration patterns; and

synthesize one or more message channels based on the detected logic integration patterns; and

generate logic integration runtime codes executable by the integration system based on the physical model graph.

9. The medium of claim 8 , the instructions further executable by the computer and configured to define the logic integration program using the data-centric logic integration language for declarative integration programming.

10. The medium of claim 9 , wherein defining a logic integration program comprises:

analyzing integration logic represented by the logical model graph; and

adding integration artifacts.

11. The medium of claim 8 , wherein the logical model graph comprises one or more annotations defined by the data-centric logic integration language as one or more nodes of the logical model graph.

12. The medium of claim 8 , wherein the logical model graph comprises no cycles.

13. The medium of claim 8 , wherein converting the logical model graph into the physical model graph comprises:

detecting patterns on the logical model graph; and

performing a rule-based transformation of the patterns on the logical model graph; and mapping into implementation-specific messaging channels.

14. The medium of claim 13 , the instructions further executable by the computer and configured to optimize the logical model graph.

15. A system, comprising:

a memory;

at least one hardware processor interoperably coupled with the memory and configured to:

receive a logic integration program comprising a plurality of logic integration patterns that are defined in a data-centric logic integration language;

generate a logical model graph based on the logic integration program, the logical model graph being runtime-independent;

bi-directionally convert the logical model graph into a physical model graph, the physical model graph being runtime-specific, wherein converting the logical model graph into a physical model graph comprises:

detect logic integration patterns of the logical model graph as detected logic integration patterns; and

synthesize one or more message channels based on the detected logic integration patterns; and

generate logic integration runtime codes executable by the integration system based on the physical model graph.

16. The system of claim 15 , the processor further configured to define the logic integration program using the data-centric logic integration language for declarative integration programming.

17. The system of claim 15 , wherein defining a logic integration program comprises:

analyzing integration logic represented by the logical model graph; and

adding integration artifacts.

18. The system of claim 15 , wherein the logical model graph comprises one or more annotations defined by the data-centric logic integration language as one or more nodes of the logical model graph.

19. The system of claim 15 , wherein the logical model graph comprises no cycles.

20. The system of claim 15 , wherein converting the logical model graph into the physical model graph comprises:

detecting patterns on the logical model graph;

optimizing the logical model graph; and

performing a rule-based transformation of the patterns on the logical model graph; and mapping into implementation-specific messaging channels.