Extending Datalog with Analytics in LogicBlox
LogicBlox is a database product designed for enterprise software development, combining transactions and analytics. The underying data model is a relational database, and the query language, LogiQL, is an extension of Datalog [13]. As such, LogiQL features a simple and unified syntax for traditional relational manipulation as well as deeper analytics. Moreover, its declarative nature allows for substantial static analysis for optimizing evaluation schemes, parallelization, and incremental maintenance, and it allows for sophisticated transactional management [11]. In this paper, we describe various extensions of Datalog for supporting prescriptive and predictive analytics. These extensions come in the form of mathematical optimization (mixed integer programming), machine-learning capabilities, statistical relational models, and probabilistic programming. Some of these extensions are currently implemented in LogicQL, while others are in either development or planning phases.