Event-Driven Data Engineering in Microservices Architectures

Event-driven data engineering in microservices architectures represents a transformative approach to building responsive and scalable systems. This architecture leverages events changes in state or updates to enable asynchronous communication between decoupled services. By implementing an event-driven architecture (EDA), organizations can achieve real-time data processing, enhancing their ability to react to changes as they occur. For instance, in a retail environment, an event-driven system can instantly update inventory levels and adjust marketing strategies based on sales transactions, fostering agility and responsiveness. The core components of EDA include event producers, which generate events; event routers, responsible for distributing these events; and event consumers, which process the events and execute necessary actions. This decoupling allows for independent scaling and deployment of services, significantly improving system reliability and reducing latency. However, challenges such as ensuring data consistency and managing event duplication must be addressed. Solutions like event sourcing and Command Query Responsibility Segregation (CQRS) can help maintain consistency across services. As organizations increasingly seek real-time insights, adopting event-driven architectures is becoming essential for enhancing business capabilities, enabling rapid decision-making, and fostering innovation in a data-centric world

Authors

Institutions

Publication Details

Journal
International Journal of Emerging Trends in Computer Science and Information Technology
Published
2025-01-01
DOI
https://doi.org/10.63282/3050-9246.ijetcsit-v6i1p104
Primary Topic
Software System Performance and Reliability
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Event-Driven Data Engineering in Microservices Architectures

Karthikeyan Muthusamy
International Journal of Emerging Trends in Computer Science and Information Technology
Software System Performance and Reliability
article

Event-Driven Data Engineering in Microservices Architectures

Karthikeyan Muthusamy
article en

Abstract

Event-driven data engineering in microservices architectures represents a transformative approach to building responsive and scalable systems. This architecture leverages events changes in state or updates to enable asynchronous communication between decoupled services. By implementing an event-driven architecture (EDA), organizations can achieve real-time data processing, enhancing their ability to react to changes as they occur. For instance, in a retail environment, an event-driven system can instantly update inventory levels and adjust marketing strategies based on sales transactions, fostering agility and responsiveness. The core components of EDA include event producers, which generate events; event routers, responsible for distributing these events; and event consumers, which process the events and execute necessary actions. This decoupling allows for independent scaling and deployment of services, significantly improving system reliability and reducing latency. However, challenges such as ensuring data consistency and managing event duplication must be addressed. Solutions like event sourcing and Command Query Responsibility Segregation (CQRS) can help maintain consistency across services. As organizations increasingly seek real-time insights, adopting event-driven architectures is becoming essential for enhancing business capabilities, enabling rapid decision-making, and fostering innovation in a data-centric world

International Journal of Emerging Trends in Computer Science and Information TechnologyVol. 6
Rhodes College (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 84%
Software System Performance and Reliability
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Event-Driven Data Engineering in Microservices Architectures — Karthikeyan Muthusamy · International Journal of Emerging Trends in Computer Science and Information Technology (2025) | TGRS Research Map | TGRS