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Comment by nathanmarz | Hacker News Reader

Being able to model a use case with tuples and relations does not mean the database can meet the performance requirements of that use case. If it can't meet the performance requirements, then the use case is unsupported. It's the same way how no single data structure or combination of data structures can support all regular programming use cases. Sometimes you need a map, sometimes you need a list, sometimes you need a set, sometimes you need a combination, and sometimes you need something completely different.

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Yep, you need Google-scale for your shitty startup from the get-go. Otherwise why bother? Especially now, when who have single servers with only a few terabytes of RAM at your disposal.

Many of the problems with databases that I outlined in that post are about how they create complexity, which is not necessarily related to performance or scale. Complexity kills developer productivity, which reduces iteration speed, which can be the difference between an application succeeding or failing.

Interesting, what if one creates multiple databases, but on the same instance (or even process group). Can these conflicting issues resolve somehow? Is there a super-proxy which would only log transaction phases and otherwise offload jobs to database servers (and sqlite wrappers)?

Basically striping-mirroring RAID but for… data.

I can imagine Codd saying the exact inverse: any sufficiently complex data model quickly becomes intractable for developers to assemble ideal indexes and algorithms together each time in response to new queries, which kills productivity and reduces iteration speed. Particularly as the scale and relative distributions of the data changes. The whole idea of declarative 4GLs / SQL is that a query engine with cost-based optimization can eliminate an entire class of such work for developers.

Undoubtedly the reality of widely available SQL systems today has not lived up to that original relational promise in the context of modern expectations for large-scale reactive applications - maybe (hopefully) that can change - but in the meantime it's good to see Rama here with a fresh take on what can be achieved with a modern 3GL approach.

In the experience of my department, event sourcing has brought complexity, not taken it away. Theoretically, when done right, by skilled and disciplined teams and to store the state of one system to build projections off of and not to publish state changes to other systems, I think it might work. But in most cases it's overkill. A big investment with an uncertain payoff.

Sometimes you just need a DBA to help you optimise your DB for your workload and future growth. In general, developers make shitty DBA's and vice versa.

As a DBA, who has managed enough monolithic databases at mid and large sized organizations, there are enough safeguards in today's date to avoid the scenario you described - backups, read replicas, replication to avoid the need for unnecessary distributed databases.

I suspect you responded to the wrong parent.

Performance tuning is not a skillset enterprise DBAs usually have.

Every DBA I've worked with has had performance tuning as one of their top skills, both at the installation-level and query-level. Sometimes it's optimizing a query using some hard-earned knowledge of the RDBMS, and sometimes it's keeping logs and data on separate storage.

And devs do?

Hell, what about the security requirements?

https://learn.microsoft.com/en-us/sql/relational-databases/s...

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