Optimizing MongoDB Performance for High-Traffic E-Commerce Applications

Optimizing MongoDB Performance for High-Traffic E-Commerce Applications

Aditi B Khanpara1, Mr. Hiren M Bhatt2

1Aditi B Khanpara Department of Information Technology & ATMIYA University

2Mr. Hiren M Bhatt Department of Information Technology & ATMIYA University

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Abstract - E-commerce is witnessing rapid growth and making a strong demand for database systems that need to be fast, scalable, and fault-tolerant. Most developers opt for MongoDB, a document-oriented NoSQL database, because of its flexibility and how it can be easily used to work with the latest web technologies. Still, database performance can be in the doldrums during peak e-commerce traffic hours, which may lead to problems such as slow page loads, high latency, and a negative user experience. It is therefore a plan in this study to investigate ways to boost to a large extent MongoDB performance, particularly for overloaded e-commerce situations. Measures like sharding, replication, query optimization, data modeling practices, and indexing are analyzed. Each method is validated with real cases and performance measurements. The purpose of this paper is the provision of useful practices to the developers so that they can use MongoDB efficiently and suitably in high-load conditions.

Key Words:  MongoDB performance, high-traffic applications, e-commerce optimization, NoSQL databases, database performance tuning, horizontal scaling, query optimization, sharding in MongoDB, write and read throughput, data indexing strategies, replica sets, load balancing in databases, backend performance, caching mechanisms, e-commerce scalability, MongoDB architecture, big data handling, e-commerce systems, cloud database performance, real-time data processing, full-stack optimization, web-scale applications, open-source database solutions