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> 3) Carefully-tuned RDBMSs are more capable than many tend to admit. So important. I have, in the past, worked with many people who simply thought NoSQL was n
by BinaryIdiot 10y ago
> 3) Carefully-tuned RDBMSs are more capable than many tend to admit.
So important. I have, in the past, worked with many people who simply thought NoSQL was new and RDMS was old therefore ALWAYS use new. Trying to get someone to pick an RDMS solution in said environment was impossible. The times I've had to take a document store and make it store relational data are more than I'd like to admit.
- deleted 10y ago[deleted]
- kaeluka 10y agoI've never worked with postgres before my current project and I'm so impressed with how easy it is to get stuff done. I used Cassandra for a prototype (bad choice for my workload, not Cassandra's fault) and documentation, ease of tuning, tooling maintenance all seem to be so much easier. Of course, Cassandra has a host of problems to solve that postgres doesn't -- being meant to run on clusters and all. But you know what, I don't care. I also was heavily leaning new stuff before. But what can I say, if an RDBMS is what I need -- I probably should use one.
- adw 10y agoI have a pet theory that any given system has a maximum cleverness budget. Make sure to spend it on the things which actually matter in your problem domain. Interesting data products often have to spend a lot of that cleverness budget in the algorithmic layer – machine learning and statistics. So when I work on that kind of thing, I've learned to have a real appreciation for boring data storage. I'll even happily use MySQL; the ways in which MySQL can suck are very well-understood and that's a hugely underappreciated virtue.
- fuck_google 10y agoOn the other hand having the right kind of data storage can greatly benefit some algorithms. For example a graph database might work better with some graph based algorithms.
- shredwheat 10y agoThis 'cleverness budget' is a fantastic term. Thank you!