[tsahyt]

There's a lot going on and that's the way it has been for quite a while now but as someone who's working with databases only marginally at the moment, I'm left wondering: What's wrong with RDBMS? Sure it's nice to have a simple Key-Value Store for applications that don't need much more than this but bottom line, the relational model is very powerful, albeit quite abstract, and most data we need to deal with can be made to fit into this model. We have a working, declarative query language that Just Works(TM), for which we have written very good optimizers. The various instances of such DMBS range from small-scale use (for example, SQLite) to really-huge (Postgres, Oracle, etc). So, to sum it up: Exactly why should we abandon this?

[lmm]

> the relational model is very powerful, albeit quite abstract, and most data we need to deal with can be made to fit into this model

Maybe, but it's awkward. Graph or tree structures are still painful to store in relational databases, and a lot of problems turn out to involve those shapes.

> We have a working, declarative query language that Just Works(TM), for which we have written very good optimizers.

Maybe, but the tooling is still terrible. Where are the libraries? Where are the IDEs? Where's the integration that makes it easy to call procedures in my application language from SQL and vice versa? General-purpose programming languages have got better and better in the last 25 years, while SQL has stayed static.

> So, to sum it up: Exactly why should we abandon this?

Look at the ORM problem. Why do people continue to use these horrific bloated, leaky tools? Because it's really nice to be able to store and query in the native language of your application. We need storage tech that's better at supporting this.

[VLM]

Most boots on the ground DBAs don't know anything about rational DB design. Codd Normal form? Whats that? Can't I just make one giant table? Indexes? Why would I want indexes? I heard they take up disk space and CPU so I won't use any, to increase performance. So they (poorly) implement key value stores regardless what the problem actually requires (if the only tool you know how to use is a nail...). Nothing funnier that watching a noob do a select * on a large table transferring gigs of data and use his RoR app to implement the WHERE using nested ruby if statements and string comparisons (or better regexes without understanding regexes, LOL) and god help me a bubble sort instead of an ORDER BY clause and of course hit another table once for each row selected from the first table because he doesn't know JOINs even exist, or heard they're "slow".

A RDBMS is a very slow key value store, so anything that can't do transactions or can't do anything else, is always going to be faster at its extremely limited set of abilities.

From an engineering perspective if you need 10 HP to run your 5 KW generator, a RDBMS is like installing a 10000 HP marine diesel and then not having any idea how to start or maintain it or even where to get the fuel. Obviously every objective performance metric would be better for a 10 HP lawnmower engine in that app, if all you'll ever plan to use is 10 HP and you have no idea how to use anything more advanced anyway.

There are also very loudly trumpeted anecdotal situations or contrived thought experiments where certain unusual technologies fit a unusual situation very well. This is, oddly enough, unusual.

I've read and experimented with the "7 DBs in 7 weeks" book and it IS very interesting but I can't find any business cases to actually use any of it, which is somewhat frustrating. And my experience is how you end up with people writing CRUD apps to store cooking recipes that none the less use NEO4J because they really, really, want to add a line to their resume that they used NEO4J, not because the app needed it.

[StefanKarpinski]

Condescend much?