Cassandra-based data repository design for food supply chain traceability

Abstract

Purpose

The purpose of this paper is to design a supply chain database schema for Cassandra to store real-time data generated by Radio Frequency IDentification technology in a traceability system.

Design/methodology/approach

The real-time data generated in such traceability systems are of high frequency and volume, making it difficult to handle by traditional relational database technologies. To overcome this difficulty, a NoSQL database repository based on Casandra is proposed. The efficacy of the proposed schema is compared with two such databases, document-based MongoDB and column family-based Cassandra, which are suitable for storing traceability data.

Findings

The proposed Cassandra-based data repository outperforms the traditional Structured Query Language-based and MongoDB system from the literature in terms of concurrent reading, and works at par with respect to writing and updating of tracing queries.

Originality/value

The proposed schema is able to store the real-time data generated in a supply chain with low latency. To test the performance of the Cassandra-based data repository, a test-bed is designed in the lab and supply chain operations of Indian Public Distribution System are simulated to generate data.

Citation

Singh, S.K. and Jenamani, M. (2021), "Cassandra-based data repository design for food supply chain traceability", VINE Journal of Information and Knowledge Management Systems, Vol. 51 No. 2, pp. 193-217. https://doi.org/10.1108/VJIKMS-08-2019-0119