Integrating Velox into TinkerPop for Graph Queries on Vectorized Engine

To enhance the query efficiency of relational databases and build a unified computing backend, Meta has developed Velox, a vectorized execution engine library based on columnar storage, Currently, there is no standardized specification for computation engine, and storage in graph databases, leading to failed to effectively utilize the vectorized processing capability of modern CPU. In this paper, we propose a middleware that primarily focuses on (1) non-invasively integrating Velox into the TinkerPop framework to provide unified vectorized engine acceleration for all graph databases supporting the TinkerPop specification; (2) conducting graph queries based on the relational data storage model, eliminating the overhead of transforming the storage model into a graph storage model; (3) validating the acceleration effect of the vectorized engine on interactive workload of graph queries under a single-node environment.