Readit NewsI've often heard that the best way to learn about customers is to put a product in front of them and see how they react. People have a hard time knowing what exactly they want in a vacuum, but once you give them something to play with, they're usually good at saying what's good and what's not.
When your system is replacing some existing system, which could well be just paper-based, it is very useful to study it carefully. It will give you a good idea about the data and its internal relations. If you want to show something to a customer, you can also simple mock-ups like static HTML pages.
Only after you have a decent understanding of the system you should start building it. There will be many new requests, but most will just be concerned with the UI. If you have the right data model and architecture, those will not be very difficult to solve.
> JIT has been used very successfully for a couple of languages, e.g. Java
I'm not at all disputing that - but its promises of "beating AOT" that we used to hear have not come to fruition. Where it really matters, e.g. HPC, you don't really see any JIT. C, C++ and Fortran still rule. And even for Java, you tend to be able to achieve equal or better performance with AOT compilers.
With an AOT compiler a lot of work is done at compile time, but with JIT it is done at runtime, which makes these programs slower to start. But for programs that do run for a longer time, like servers or IDE's the performance is quite decent. But Java is a memory safe language which means that it has to do a lot of checks that unsafe languages do not have to do, which means that it will always be slower that unsafe languages. In some cases the JIT can eliminate those safety checks, but that is not always possible.
Java always had (and still has) an AOT that compiled to byte code. Adding JIT was a major improvement.
I think the problem of this essay is that it's overly technical: only those versed well enough in SQL will really care to read the whole thing, and if they are already at that level, either they accepted that "SQL will get the job done in the end", or they learned to live along it and now even kinda embrace it, and are happy to write about how the examples are very poor and dismiss the critique based on that, when the essay kinda explains it main point pretty well:
>> The core message [...] is that there is potentially a huge amount of value to be unlocked by replacing SQL
To me, a lot of people defends SQL saying that "perfect is the enemy of good" and that SQL simply works. Not the favourite of anyone, but everyone kinda accepts it.
And yeah, it's true. People use SQL because it's good enough, and trying to reinvent the wheel would take more work (individually speaking) than just dealing with SQL as it is right now. For large organizations where the effort could be justified, all your engineers already know SQL anyway, so it's not so great either.
But for something so relevant as relational databases, perfect is not the enemy of good. We do deserve better. We generally agree that SQL has many pitfalls, it's not great for any kind of user (for non-technical users, a visual programming language would work well here, more like what Airtable does, closing the bridge between spreadsheet and hardcore database, and for technical users, it does feel unwieldy and quirky). We should be more open to at least consider critiques and proposals for better. We might find out that people, from time to time, are making some good points.
We certainly do deserve better, and the author made some good suggestions.
Unfortunately, building a new database is a huge project and there appears to be no party currently willing to sponsor it.
I think it's important to distinguish between what's highly optimizable in theory and what's easily optimizable in practise. The latter working here and now, and the latter being a (possibly perpetual) decade of compiler development away.
An example here is how, sure, in theory, JITs can outpace AOT compilation because they have all the information the AOT compiler has plus runtime insights. But the ability to truly do that always seems to be a decade of compiler development away, with many giving up on the idea entirely.
It's also important to consider what we're comparing SQL's optimizability against. If it's against typical NoSQL databases, most of which seem to favour a lower-level query specification, I can defend SQL's optimizability to the end - with SQL databases having the freedom to dynamically switch algorithms to adapt to the actual contents of the database at the time of the query. Something which, ironically, a stale optimizer hint (i.e. written with the size & shape of the database as it was last year in mind) can actually get in the way of. Not that I'm saying that SQL planners never produce stupid query plans of course.
> An example here is how, sure, in theory, JITs can outpace AOT compilation because they have all the information the AOT compiler has plus runtime insights. But the ability to truly do that always seems to be a decade of compiler development away, with many giving up on the idea entirely.
JIT has been used very successfully for a couple of languages, e.g. Java. But adding it requires a lot of effort. The same thing is unfortunately true for new query languages, building a new database is really expensive, this is probably the main reason that there have been no serious alternatives to SQL.
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