Foundations for Architecting Data Solutions

Chapter 2. Evaluating and Selecting Data Management Solutions

You’re likely already aware of the importance of technology selection when embarking on a new project. Choosing the correct solutions is a complex process that will have long-lasting impacts on your organization and a direct impact to the success (or failure) of your data projects. Do you reuse trusted solutions, do you try something new, or do you follow examples of leaders in the industry? There are difficult decisions we must face when selecting solutions.

As you move through this decision-making process, you’ll likely be presented with market hype, extravagant promises from vendors, analysts with varied agendas, and tools with enthusiastic user bases. Some of these solutions might be good fits for your projects, whereas others will be poor fits that lead to wasted time, money, and frustration.

The goal of this chapter is to help guide you to the best choices as you move through the technology selection process. We begin by discussing some common life cycles of open source projects; this knowledge will help in understanding how healthy a project is, where it is in the life cycle, and whether it’s a potential fit regardless of the hype that might or might not accompany the project. Then, we talk about how to evaluate claims, such as the results of performance or benchmark testing. Lastly, we dig into different patterns for picking the right technologies for your projects.

A natural question to ask is: why focus on ...