Real-Time Analytics with Kafka and AWS Lambda

Real-time analytics has become an essential component in modern enterprises, enabling businesses to process and analyze data as it is generated. Apache Kafka and AWS Lambda offer a powerful combination for building scalable, serverless, and event-driven real-time analytics solutions. This paper explores how Kafka can be integrated with AWS Lambda to achieve near-instantaneous data processing, discussing architecture, implementation strategies, scalability considerations, and security challenges. Additionally, we analyze use cases, performance benchmarks, and future trends in real-time analytics.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2025-03-15
DOI
https://doi.org/10.36948/ijfmr.2025.v07i02.39039
Primary Topic
Time Series Analysis and Forecasting
Type
article
Field-Weighted Citation Impact
0.00
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article

Real-Time Analytics with Kafka and AWS Lambda

Raju Dachepally
International Journal For Multidisciplinary Research
Time Series Analysis and Forecasting
article

Real-Time Analytics with Kafka and AWS Lambda

Raju Dachepally
article en

Abstract

Real-time analytics has become an essential component in modern enterprises, enabling businesses to process and analyze data as it is generated. Apache Kafka and AWS Lambda offer a powerful combination for building scalable, serverless, and event-driven real-time analytics solutions. This paper explores how Kafka can be integrated with AWS Lambda to achieve near-instantaneous data processing, discussing architecture, implementation strategies, scalability considerations, and security challenges. Additionally, we analyze use cases, performance benchmarks, and future trends in real-time analytics.

International Journal For Multidisciplinary ResearchVol. 7(2)
Openalex Percentile: Top 95%
Time Series Analysis and Forecasting
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Real-Time Analytics with Kafka and AWS Lambda — Raju Dachepally · International Journal For Multidisciplinary Research (2025) | TGRS Research Map | TGRS