When we design software or databases, we have to make decisions right now. If you work in as many environments as I have, this means I’m often picking a tool, platform, version, technology, or something else without a complete set of information. In some cases, I’m actually writing code (SQL or C#/Java/etc.) without completely knowing the business problem I’m solving. I do know what someone described, but as many of us find out, those descriptions often prove to be lacking.
Over time, we refine the code with feedback from users, which is why DevOps has become so popular. We write the best code we can and then quickly alter code if we haven’t hit the mark. We constantly adjust by making small changes and improvements.
However, changing the code is one thing. Changing more fundamental technology choices is harder. There is an interesting post on the disproportionate impact of your early tech decisions from one of the developers at Stripe. One of the examples given is for the database platform, which was Mongo. The piece notes that once the database platform is chosen, most groups never switch platforms. I think that’s been true in many places I’ve worked. The same thing for languages and cloud providers as well, as once a choice is made, rarely does a team, much less an organization, switch.
Why is this? Is the cost of switching that high? I think it is. I’ve seen a few organizations want to migrate from a licensed relational platform to one that is free and OSS. However, the time it takes to rewrite code, the time to build new expertise, learn the tips and tricks for a new database (or other platform technology) is significant. A team can make no shortage of mistakes during this process. Is that worth the cost of licensing? Perhaps. Perhaps not. It’s a hard thing to decide. With the high cost of labor, I think it’s hard to make a good argument to rewrite.
In many cases, I’d argue that core changes to your technology stack ought to be considered, but understanding that no tech will solve all your problems and you will make lots of mistakes in the process of changing. Does this mean you need to make a great decision when you start working on a project? In my mind, no. Make the decision to use what your team is most familiar with and then live with it.
And be open to using targeted technology for specific needs. Lots of transient data in a busy workload? Add Redis to your database stack. If you need full-text search, consider ElasticSearch. Maybe add a graph database (not SQL Server) if you need queries in this problem domain. Use what works, and learn to use it well.
That last sentence might be the most important. Any technology can likely support most workloads, but you need to write good code and learn to use the platform well.
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