Gaonkar, Neha and Samimi, Parnia and Bhogal, Jagdev and Porter, Luke and Squire, Rob
(2024)
Optimized Model of Ledger Database Management to handle Vehicle Registration.
In: 2023 IEEE International Conference on Big Data (BigData), 15th - 18th December 2023, Sorrento, Italy.
Abstract
In recent years, versioning of business data has become increasingly important in enterprise solutions. In the context of big data, where the 5Vs (Volume, Velocity, Variety, Value, and Veracity) play a pivotal role, the management of data versioning gains even greater significance. As enterprises grapple with massive volumes of data generated at varying velocities and exhibiting diverse formats, ensuring the accuracy, completeness, and consistency of data throughout its lifecycle becomes paramount. System of record solutions, which cover most enterprise solutions, require the management of data life history in both system and business time. This means that information must be stored in a way that covers past, present, and future states, such as a contract with a start date in the past and an end date in the future that may require correction at any point during its lifetime. While some systems offer transaction time rollback features, they do not address the business life history dimension of a contract or asset, which requires the developer to code the business rules of the requirements. The relational data model is unable to inherently use relational constraints where a business time dimension of the data is required, as it is a “current view” and not designed for this purpose. Therefore, there is a need for better autonomous capabilities for version control of data, which will bring new functionality and cost reduction in application development and maintenance, reduce coding complexity, and increase productivity. This paper presents an approach to relational data management that relieves the developer from the need to code the business rules for versioning. The framework, called Ld8a, works with a standard Oracle database that keeps the developer in the “current view” paradigm but allows them to specify the point in time that logical insert, update, and delete events take place with the infrastructure autonomously maintaining relational correctness of the dataset across time. The Ld8a framework has been used to address the vehicle registration scenario used by AWS in presenting the capabilities of the Quantum Ledger Database product. This approach offers a solution that maintains referential integrity by the infrastructure across time, making version control of data easier and more efficient for developers.
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