This paper introduces MELOGRAPH, a new system that exposes in the front-end a domain specific language(DSL) for graph processing tasks and in the back-end identifies, ranks and generates source code for the top-N ranked en-gines. This approach lets the specialized MELOGRAPH be part of a more general multi-engine workflow optimizer. The candidate execution engines are chosen from the contempo-raneous Big Data ecosystem: graph databases (e.g. Neo4j, TitanDB, OrientDB, Sparksee/DEX) and robust graph pro-cessing frameworks with Java API or packaged libraries of algorithms (e.g. Giraph, Okapi, Flink Gelly, Hama, Grem-lin). As MELOGRAPH is work in progress, our current paper stresses upon the state of the art in this field, pro-vides a general architecture and some early implementation insights.