Data Mesh : Transactional vs Analytical workload

Date : Publié par

In the past few decades, the way we handle data has changed a lot, moving from a centralized model to a distributed and scalable approach. One of the new ideas that came out of this is called Data Mesh. This new implementation pattern requires managing both transactional and analytical workloads. This article explores the differences between these two types of workloads within a distributed and scalable approach to data management.

Autres sujets qui pourraient vous intéresser

Event Driven Architecture Introduction

Date : Publié par
The world is changing. Companies now run global businesses that span the globe and hop between clouds, breaking down silos to create seamless applications that work together for the good of the organization. This continuous state of change means that legacy architectures are insufficient or unsuitable to meet the needs of the modern organization. Applications must be able to run 24×7 with 5-9s (uptime of 99.999%), as well as be superelastic, global and cloud native.