Optimizing Cost and Performance in Serverless Databases: A Practical Framework for DynamoDB IA Mode Migration

Authors

  • Sindhu Gopakumar Nair

Keywords:

Migration, Cost, Database, DynamoDB, Server, AI, Optimization

Abstract

The paper examines the ways of minimising cost and maintaining good performance in the Amazon DynamoDB when the Infrequent Access (IA) mode is used. Most firms end up paying a great deal in serverless databases since data are being stored even when it is not frequently utilized. In response to this, the paper develops a simple framework that would be used to transfer such data into IA mode. In the study, the quantitative approach is used and two setups are compared, namely standard mode and IA mode, at the same workloads. The logs of latency, throughput and cost are sampled in seven days time. It is demonstrated that with IA mode, it is possible to reduce the cost of storage and operation by approximately 40 percent without increasing the average latency more than 10 milliseconds. The framework involves well defined steps such as the analysis of access pattern, capacity planning and latency testing. The results confirm that this way of migration is able to cost-effectively save performance without damaging it. The study can assist developers, cloud architects, and DevOps, to design intelligent cost-reduction in serverless database platforms.

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References

Bilal, M., Canini, M., Fonseca, R., & Rodrigues, R. (2021). With great freedom comes great opportunity: rethinking resource allocation for serverless functions. arXiv (Cornell University). https://doi.org/10.48550/arxiv.2105.14845

Kang, R., Chen, Y., Liu, Y., Jiang, F., Li, Q., Ma, M., Liu, J., Zhao, G., Zhang, T., Chen, J., & Zhang, L. (2025, May 12). ABase: the Multi-Tenant NoSQL Serverless Database for Diverse and Dynamic Workloads in Large-scale Cloud Environments. arXiv.org. https://arxiv.org/abs/2505.07692

Oloruntoba, O., Fakunle, S. O., Wahab, B., & Ogunsanmi, B. L. (2023). Impact of Database Migration on Application Performance : A Case Study of Database Migration from AWS to GCP. International Journal of Scientific Research in Science Engineering and Technology, 424–436. https://doi.org/10.32628/ijsrset25122168

Elhemali, M., Gallagher, N., Gordon, N., Idziorek, J., Krog, R., Lazier, C., Mo, E., Mritunjai, A., Perianayagam, S., Rath, T., Sivasubramanian, S., Sorenson, J. C., III, Sosothikul, S., Terry, D., & Vig, A. (2022). Amazon {DynamoDB}: a scalable, predictably performant, and fully managed {NoSQL} database service. https://www.usenix.org/conference/atc22/presentation/vig

Hillenbrand, A., Störl, U., Nabiyev, S., & Klettke, M. (2021). Self-adapting data migration in the context of schema evolution in NoSQL databases. Distributed and Parallel Databases, 40(1), 5–25. https://doi.org/10.1007/s10619-021-07334-1

Störl, U., Klettke, M., University of Hagen, Germany, & University of Rostock, Germany. (2022). Darwin: a data platform for NoSQL schema evolution management and data migration. In Workshop Proceedings of the EDBT/ICDT 2022 Joint Conference [Conference-proceeding]. https://ceur-ws.org/Vol-3135/dataplat_short3.pdf

Bonnet, O. & University of Florida. (2024). COST-PERFORMANCE OPTIMIZATION IN SERVERLESS COMPUTING [Article]. https://www.researchgate.net/publication/396211342

Győrödi, C. A., Dumşe-Burescu, D. V., Zmaranda, D. R., Győrödi, R. Ş., Gabor, G. A., & Pecherle, G. D. (2020). Performance Analysis of NoSQL and Relational Databases with CouchDB and MySQL for Application’s Data Storage. Applied Sciences, 10(23), 8524. https://doi.org/10.3390/app10238524

Saxena, N. S. (2025). Serverless Architectures: Redefining scalability and cost optimization in cloud computing. Journal of Information Systems Engineering & Management, 10(58s), 625–632. https://doi.org/10.52783/jisem.v10i58s.12642

Maamari, S. R. S. A., & Nasar, M. (2025). A Comparative Analysis of NoSQL and SQL Databases: Performance, Consistency, and Suitability for Modern Applications with a Focus on IoT. A Comparative Analysis of NoSQL and SQL Databases: Performance, Consistency, and Suitability for Modern Applications With a Focus on IoT, 1(2), 10–15. https://doi.org/10.63496/ejcs.vol1.iss2.76

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Published

31.10.2025

How to Cite

Sindhu Gopakumar Nair. (2025). Optimizing Cost and Performance in Serverless Databases: A Practical Framework for DynamoDB IA Mode Migration. International Journal of Intelligent Systems and Applications in Engineering, 13(1s), 388 –. Retrieved from https://www.ijisae.org/index.php/IJISAE/article/view/7904

Issue

Vol. 13 No. 1s (2025)

Section

Research Article

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