What question did this study set out to answer?

The aim is to explore principles and technologies that enable real-time data processing in distributed environments.

April 21, 2026Open Access

A Study On Real-Time Data Processing In Distributed Systems

View Full Paper

Ask AI

Bookmark

Authors

Explores real-time data processing in distributed systems, highlighting its significance in various sectors.

The aim is to explore principles and technologies that enable real-time data processing in distributed environments.
Examined frameworks like Apache Kafka, Flink, Spark Streaming, and Storm.
Discussed challenges including latency management, scalability, and data synchronization.
Analyzed the role of real-time analytics in various sectors.
Efficient real-time data processing is crucial for responsive and scalable systems.
Frameworks demonstrated the capability to handle high-velocity data streams with low latency.
Identified strategies to address challenges like system reliability and data consistency.

Meera Iyer (2019) studied this question.

View Full Paper

Ask AI

Bookmark