Modeling and In-Database Management of Relational, Data-Aware Processes (Extended Version)

TL;DR

This paper introduces a fully SQL-based, declarative approach for modeling, verifying, and executing relational data-aware processes directly within relational databases, enhancing integration and agility.

Contribution

It presents a novel in-database, SQL-grounded framework for integrated process modeling, verification, and enactment on relational data, with automatic translation to executable SQL.

Findings

Implemented a working prototype demonstrating feasibility

Supports process enactment with or without logging

Enables integrated verification and management within relational databases

Abstract

During the last two decades, it has been increasingly acknowledged that the engineering of information systems usually requires a huge effort in integrating master data and business processes. This has led to a plethora of proposals, both from academia and the industry. However, such approaches typically come with ad-hoc abstractions to represent and interact with the data component. This has a twofold disadvantage. On the one hand, they cannot be used to effortlessly enrich an existing relational database with dynamics. On the other hand, they generally do not allow for integrated modelling, verification, and enactment. We attack these two challenges by proposing a declarative approach, fully grounded in SQL, that supports the agile modelling of relational data-aware processes directly on top of relational databases. We show how this approach can be automatically translated into a concrete procedural SQL dialect, executable directly inside any relational database engine. The translation exploits an in-database representation of process states that, in turn, is used to handle, at once, process enactment with or without logging of the executed instances, as well as process verification. The approach has been implemented in a working prototype.