About This Article
This is an AI-generated summary of a research paper. The original authors did not write or review this article. See full disclosure ↓
Overview
This research examines the application of incrementally-refreshed materialized views (IMMV) in corporate database systems, specifically within the context of marketplace relational database architectures. The study evaluates the operational tradeoffs of implementing IMMV by measuring transaction throughput and query execution performance in a PostgreSQL environment configured with a marketplace schema.
Methods and approach
A computational experiment was conducted using PostgreSQL to establish a database schema representative of marketplace operations. Multiple incrementally-refreshable materialized views were created, with incremental refresh mechanisms implemented via Python. Performance metrics were captured across two primary dimensions: transactions per second (TPS) as a measure of write-intensive workload capacity, and query execution duration for read operations against both base tables and materialized views. Comparative analysis examined query performance under repeated execution scenarios versus materialized view access patterns.
Results
Experimental findings demonstrate a near-linear degradation in system TPS as the quantity of IMMV increases, indicating cumulative computational overhead in transactional processing. Conversely, data retrieval operations from materialized views exhibit substantial acceleration, with execution times improving by more than two orders of magnitude in certain scenarios and executing in constant time regardless of underlying data volume. Specific analytical monitoring scenarios—including customer average order value computation and aggregate monthly sales calculations—demonstrated measurable latency reduction when materialized views are queried compared to recalculation of base queries.
Implications
IMMV deployment introduces a fundamental performance tradeoff between transactional write efficiency and analytical read latency. While materialized views substantially improve query response times for complex analytical operations, the associated penalty on transaction processing throughput necessitates careful evaluation against system requirements. The technology exhibits practical value primarily in scenarios characterized by frequent complex analytical queries operating against relatively stable transactional data. Implementation introduces additional system complexity through enhanced interdependency between components and potential fragility related to synchronization failures during incremental refresh operations. Organizations implementing IMMV must carefully assess workload characteristics, transaction frequency, and analytical query complexity to justify the incurred tradeoffs.
Disclosure
- Research title: Переваги та недоліки застосування інкрементально-оновлюваних матеріалізованих подань у корпоративних застосунках
- Authors: Б. Е. Панченко, Томас Олексійович Пасенченко
- Publication date: 2026-02-26
- DOI: https://doi.org/10.34229/1028-0979-2026-1-5
- OpenAlex record: View
- Image credit: Photo by Bernd 📷 Dittrich on Unsplash (Source • License)
- Disclosure: This post is an AI-generated summary of a research work. It was prepared by an editor. The original authors did not write or review this post.