In this text, I aim to delve into the varied kinds of data platform architectures, taking a greater take a look at their evolution, strengths, weaknesses, and practical applications. A key focus can be the Data Mesh architecture, its role in Modern Data Stack (MDS) and today’s data-driven landscape.
It’s a well known indisputable fact that the architecture of an information platform profoundly affects its performance and scalability. The challenge often lies in choosing an architecture that best aligns together with your specific business needs.
Given the overwhelming multitude of information tools available available in the market today, it’s easy to wander off. The Web articles I see every now and then on this topic are sometimes highly speculative. Questions on which tools are best, who leads the industry, and make the appropriate selection will be very frustrating. This story is for data practitioners who would love to learn more about data platform design and which one to decide on in each scenario.
Modern data stack
I keep hearing this term on almost every data-related website on the Web. Each LinkedIn data group offers a dozen of posts on this topic. Nonetheless, nearly all of those cover just the info tools and don’t emphasize the importance of…
