Real-Time Data Streaming and Analysis Using SQL Server with Apache Kafka

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Noman Mazher
Hadia Azmat

Abstract

Real-time data streaming and analysis have become pivotal in today’s data-driven world, enabling businesses to derive immediate insights and make timely decisions. Apache Kafka and SQL Server, two powerful technologies, provide a robust framework for handling high-volume, low-latency data streams and performing real-time analytics. Apache Kafka, a distributed event streaming platform, is ideal for ingesting and processing large streams of data, while SQL Server offers strong transactional consistency, robust querying capabilities, and analytical power. This paper explores the integration of SQL Server with Apache Kafka for real-time data streaming and analysis. It discusses the architecture, key concepts, and best practices for leveraging both systems to efficiently handle streaming data, perform real-time analytics, and make informed business decisions. The paper also addresses the challenges and solutions associated with this integration, such as data synchronization, fault tolerance, and system performance, while showcasing real-world use cases of SQL Server and Apache Kafka in diverse industries.

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How to Cite
Mazher, N., & Azmat, H. (2024). Real-Time Data Streaming and Analysis Using SQL Server with Apache Kafka. Pioneer Research Journal of Computing Science, 1(3), 44–52. Retrieved from http://prjcs.com/index.php/prjcs/article/view/41

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