Comment by peschkaj | Hacker News Reader

Comment by peschkaj | Hacker News Reader

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I think we're in agreement writing applications in the database isn't a good idea.

By "empirical proof", I mean that I have never seen anyone conclusively prove that switching data access from stored procedures to ad hoc SQL through an application was the cause of performance improvement. I've seen proof that removing complex application logic from the database fixed a problem, or that better indexing improved performance, but I've never seen anyone prove that removing stored procedures alone fixed the problem.

Further, there's nothing in your proposed solution of scaling out with readable replicas that precludes the use of stored procedures for data access. As a huge fan of both databases and separation of concerns, stored procedures make tremendous sense. They let a domain expert tune the database as needed. Even going so far as allowing that expert to re-write queries, provide optimizer hints, or even change the physical data model for better performance without ever changing application code.

Although I may or may not be competent, I have scaled "stuff" in a database. But I do appreciate you getting a vague ad hominem into the first sentence. Bravo.

The typical bottlenecks that I found were almost always IO - either through crappy storage, crappy indexing, or some combination of the two. Modern databases typically aren't bottlenecked by the lock manager.

I'd also agree that moving work out to a NoSQL database is particularly tricky. For three years I maintained the .NET Riak client and helped developers make better decisions when they were considering moving away from an RDMBS.

Scalability IS NOT performance.

I like to say that scalability is like a Mac truck. Good if you have to move a lot of stuff, but not necessarily the best tool for getting your groceries. Moving logic from stored procedures to the application adds latency and network traffic. This is never going to be good for how fast you process an individual request. However it can let your system handle more requests per second.

That's only true if there aren't resources taken up by your in-flight transactions, and if those resources don't exceed the cost of just running the logic in-place. Otherwise, you're not sacrificing latency for throughput, you're just sacrificing latency and throughput. Unless you have a very heavy application-level thing to do that doesn't require periodic new access to data, that's usually not the case, especially if you're trying to process requests at line rate (NIC queues will get exhausted just trying to hold all the pending requests in memory, and you'll start to suffer from lock manager contention, page buffer swapping, etc.).

True.

But my experience with Oracle specifically is that handling connections is just general overhead, while the real failure modes have to do with overloading random latches somewhere deep inside of the system. I also found that logic in stored procedures caused us to hit limits faster than leaving it in the application.

The specific case I saw this in was a simple set of queries to test if you were in an A/B test, and if not to assign you to a random variant. After I left my application logic was moved into a complex stored procedure, and they then had scalability limitations that they didn't have before. For political reasons they declared success and ran fewer A/B tests...

(I've used a lot of other databases as well, but Oracle is the only one I've really pushed to its scalability limits.)

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