I continue to be surprised by the number of hackers who don't know SQL well. And when developers say you can only really benefit with RDBMS when you have petabytes of data, I wonder if they haven't worked on apps that are explicitly data-centric. Granted, I spend my work days in apps that are or closely resemble data warehouses, but I can get your standard RDBMS engine to do a tremendous amount of work before I have to touch the first line of procedural code. If it fits your needs, by all means jump feet first into the RDBMS of your choice. When it doesn't fit, know enough to realize it and make a considered decision (seldo, +1 for mentioning the huge number of apps that don't need RDBMS)

The point I'm really trying to express is that any hacker that touches a database would probably be well served to spend some minimal amount of effort learning ANSI SQL and understanding basic indexing, basic normal forms, and maybe star schemas. Adding some intermediate SQL and RDBMS skills to your toolbox is just another step towards maximizing your effectiveness as a developer.

No. Not because it's complicated. Because they wanted higher level facilities for getting/setting data. In other words, they put in abstraction because abstraction is good, not because they are dumb.

I suspect that a big part of the problem with SQL is that it's too abstract: it is both hard to predict how fast a query will run and hard to predict whether the query will continue to run fast as the database changes. A big part of the appeal of things like memcached and Redis is that their performance is not only fast, but also predictable.

No, it's a higher level facility for querying data when you want different result sets back randomly, it sucks most common operations of inserting or updating data.

Forcing me to write a very long statement to insert a row isn't in any way more abstract that saying anObject.save().

SQL continually forces one to write the same boring code over and over. As soon as you start automating the generation of the boring bits, you've started to build an ORM. ORMs exist because programmers get tired of writing the same code again and again.

While SQL is good at what it does, it doesn't do the thing programmers need done most, which is store data structures easily without making them write a bunch of mapping code to translate it first. SQL isn't confusing, it's just frustratingly boring and repetitive.

The people who made the frameworks would require a good understand as well as the idea that an abstraction might make life easier.

The side effect is that if you create a good enough abstraction you'll get people who can handle the abstraction but are a little shakey when dealing with what is abstracted.

See, you can both be right :)

The reason, say, C++ is a good abstraction for machine code is because it simplifies what's going on to the point that you can write something very complex in fewer lines of code, allowing it to fit into the human brain better. I'm willing to be shown examples to the contrary, but ORM layers don't simplify or compress relational queries, they just change the syntax to something more "object-y".

So maybe my point is that abstraction is good, but ORM isn't really abstraction.

Microsoft's Linq for SQL generates mostly OK SQL from your code. While not perfect for all complex operations (like multiple joins with aggregations), the SQL isn't horrible. For most use cases though, the SQL seems to be on par with what I would write myself. Ofcourse this is a rather vendor-specific implementation (for Microsoft SQL Server), but there are decent ORMs out there.

The biggest problem really comes when people don't understand what underlying SQL will be required for specific operations and just write code blindly. This can cause things like the famous nested-loops effect instead of efficient joins, but this is solvable trough knowing how to properly use your tool.

That being said ORMs are good at poking at small amounts of data (single or few objects), while SQL is probably the best language there is for huge set-based operations. When you are doing set-based things, not using SQL will most likely be a bad choice.

Web developers on these types of projects cannot either a: buy a "real" SQLDBMS, or b: charge their customers so their business model makes sense without a huge number of transactions. This means they are willing to suffer it out with solutions that don't provide flexibility or data correctness guarantees of a RDBMS.

This is just a guess, but it's quite likely that it is the rise of hyper-scale-intensive, speed-intensive, revenue-light business models that drives devs towards deciding SQL isn't worth it.

I'm not going to claim it's perfect, but it's pretty damn good, and postgres + intelligently used caching (such as memcached) goes a long way.

My code was hard to understand (and very hard to write, at times) but the result was a much lighter, much faster application.