🧭Business Intelligence: Monolithic vs. Distributed Architecture (Part II: Architectural Choices)

Business Intelligence Series

One metaphor that can be used to understand the difference between monolith and distributed architectures, respectively between data warehouses and data mesh-based architectures as per Dehghani’s definition [1] - think that you need to accommodate 500 families (the data products to be built). There are several options: (1) build a skyscraper (developing on vertical) (2) build a complex of high buildings and develop by horizontal and vertical but finding a balance between the two; (3) to split (aka distribute) the second option and create several buildings; (4) build for each family a house, creating a village or a neighborhood. 

Monolith vs. Distributed Architecture - 500 families

(1) and (2) fit the definition of monoliths, whiles (3) and (4) are distributed architectures, though also in (3) one of the buildings can resemble a monolith if one chooses different architectures and heights for the buildings. For houses one can use a single architecture, agree on a set of predefined architectures, or have an architecture for each house, so that houses would look alike only by chance. One can also opt to have the same architecture for the buildings belonging to the same neighborhood (domain or subdomain). Moreover, the development could be split between multiple contractors that adhere to the same standards.

If the land is expensive, for example in big, overpopulated cities, when the infrastructure and the terrain allow it, one can build entirely on vertical, a skyscraper. If the land is cheap one can build a house for each family. The other architectures can be considered for everything in between.

A skyscraper is easier for externals to find (mailmen, couriers, milkmen, and other service providers) though will need a doorman to interact with them and probably a few other resources. Everybody will have the same address except the apartment number. There must be many elevators and the infrastructure must allow the flux of utilities up and down the floors, which can be challenging to achieve.

Within a village every person who needs to deliver or pick up something needs to traverse parts of the village. There are many services that need to be provided for both scenarios though the difference it will be the time that's needed to move in between addresses. In the virtual world this shouldn't matter unless one needs to inspect each house to check and/or retrieve something. The network of streets and the flux of utilities must scale with the population from the area.

A skyscraper will need materials of high quality that resist the various forces that apply on the building even in the most extreme situations. Not the same can be said about a house, which in theory needs more materials though a less solid foundation and the construction specifications are more relaxed. Moreover, a house needs smaller tools and is easier to build, unless each house has own design.

A skyscraper can host the families only when the construction is finished, and the needed certificates were approved. The same can be said about houses but the effort and time is considerably smaller, though the utilities must be also available, and they can have their own timeline.

The model is far from perfect, though it allows us to reason how changing the architecture affects various aspects. It doesn't reflect the reality because there's a big difference between the physical and virtual world. E.g., parts of the monolith can be used productively much earlier (though the core functionality might become available later), one doesn't need construction material but needs tool, the infrastructure must be available first, etc. Conversely, functional prototypes must be available beforehand, the needed skillset and a set of assumptions and other requirements must be met, etc.

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References:
[1] Zhamak Dehghani (2021) Data Mesh: Delivering Data-Driven Value at Scale (book review)