Author
Abstract
The technical challenges and practical solutions for scaling big data applications in MongoDB with a real-time environment are examined in this document. Current relational databases find it difficult to work with rigid schemas and vertical scale limitations, which prevents them from processing high velocity, high volume, and heterogeneous data. MongoDB’s document-oriented architecture also provides flexibility and good horizontal scaling by sharding. Dynamic shard rebalancing, inbuilt replication, and automated failover are all key features combined to achieve high availability and low latency. The study explains how data is made to span across, and more efficiently, several servers without bottlenecks while optimizing query performance for mission-critical applications. Moreover, the report explores integration with more advanced technologies like machine learning and artificial intelligence, enabling database analytics for real-time decision-making. Enhanced indexing strategy and efficient aggregation framework facilitate fast retrieval and sophisticated data processing. MongoDB has proven to be the perfect technique for managing heavy, diverse real-world case studies such as e-commerce/game deployments while providing personalized experiences, competitive performance, and smart infrastructure management. It supplies technical insights and concrete methodology to build highly scalable, real-time big data solutions with MongoDB. This points the reader to the fact that the shard key selection should be really careful, with the performance constantly monitored and cloud-based auto-scaling so that they will have to operate as per the changing business requirements. By leveraging these efficiency, scalability, and resilience features, organizations achieve efficiency, scalability, and resilience in processing real-time data streams. In essence, this study offers a reference guide for IT professionals and decision-makers placing MongoDB in environments requiring continuous innovation and rapid response.
Suggested Citation
Mukesh Reddy Dhanagari, 2024.
"Scaling with MongoDB: Solutions for Handling Big Data in Real-Time,"
Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 6(5), pages 246-264, October.
Handle:
RePEc:alk:jcsts0:v:6:y:2024:i:5:id:8931
DOI: 10.32996/jcsts.2024.6.5.20
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