Real-time Analytics on AWS and Google Cloud to Unlock Data Driven Insights
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Research Paper | Computer Science & Engineering | United States of America | Volume 13 Issue 11, November 2024 | Popularity: 5.9 / 10


     

Real-time Analytics on AWS and Google Cloud to Unlock Data Driven Insights

Anudeep Kandi, Maria Anurag Reddy Basani


Abstract: This study comprehensively analyzes Amazon Web Services (AWS) and Google Cloud in supporting real-time analytics and machine learning (ML) integration. We utilized transactional data from the Kaggle ?Credit Card Fraud Detection? dataset. The experiment evaluates both platforms? metrics: ingestion latency, data processing efficiency, ML inference latency, scalability, and cost-effectiveness. AWS and Google Cloud were configured with identical virtualized hardware environments to ensure replicable results. Findings show that AWS consistently outperformed Google Cloud. It suppressed with an average ingestion latency of 116.1 ms compared to Google Cloud?s 125.2 ms and a 10.8% faster query processing time. AWS SageMaker also demonstrated a 15.8% reduction in ML inference latency over Google Cloud?s AI Platform. Scalability tests revealed that AWS maintained stable performance at ingestion rates exceeding 2,500 records per second. It surpassed Google Cloud?s limit of 2,000 records per second. Cost analysis further indicated AWS?s marginal cost advantage in data processing and ML inference. Results were validated against baseline metrics from existing literature. It confirms that AWS offers a more efficient, cost-effective solution for real-time, ML-integrated analytics, particularly in high-load environments.


Keywords: Real-time analytics, Amazon Web Services, Google Cloud, ML integration, ingestion latency, data processing efficiency, scalability, cost-effectiveness, cloud-based data analytics, high-frequency data environments


Edition: Volume 13 Issue 11, November 2024


Pages: 302 - 308


DOI: https://www.doi.org/10.21275/SR241105211600


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Anudeep Kandi, Maria Anurag Reddy Basani, "Real-time Analytics on AWS and Google Cloud to Unlock Data Driven Insights", International Journal of Science and Research (IJSR), Volume 13 Issue 11, November 2024, pp. 302-308, https://www.ijsr.net/getabstract.php?paperid=SR241105211600, DOI: https://www.doi.org/10.21275/SR241105211600

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