1) Hierarchical data. The relational model is fine here, but the query syntax isn't awesome.
2) Understanding remote data. This is outside the scope of the data model, but it does effect the way software is built.
Neither of these show any evidence that the relational model should be replaced.
There are many more issues, you've just gotten used to eating SQL turds. Hierarchical data is solved by CTEs, so that's not a big deal.
The bigger deal is that relations themselves are impoverished second-class citizens. This means you can't write a query, bind it to a variable and then reuse that query to build another query or store that query in a table column. Something like:
var firstQuery = select * from Foo where ...
var compositeQuery = select * from firstQuery where ...
create table StoredQuery(id int not null primary key, query relation)
insert into StoredQuery values (0, firstQuery)
Then there's pervasive NULL, inconsistent function and value semantics across implementations, and a few other issues.
How would the database engine efficiently resolve any references to the embedded relation ?
I'm also having trouble understanding how your INSERT statement would even work - is the firstQuery being inserted being treated as hierarchical data where every single relation attached to every single row has its own schema/structure ? Or is the structure fixed in the CREATE TABLE statement so that you can't use just any relation, but rather have to use a relation that conforms to the structure defined in the CREATE TABLE statement ?
Relations are functions over these sequences. The embedded relation is then a stored function over a set of nested sequences. So to add the concrete types:
var firstQuery = select Id, Name, Payment from Foo where ...
var compositeQuery = select Id, Name, Total from firstQuery where ...
create table StoredQuery(id int not null primary key, query relation{Id int, Name Text, Payment decimal})
insert into StoredQuery values (0, firstQuery)
But first-class relations would also present some optimization challenges, so a subset of a relational system with a restricted form of first-class relations corresponding to materialized views that can be stored in table columns and used in queries would get pretty close.
Apache Spark is the best example I've seen of this in that you can compose schemas on the fly and it will unroll them at the end based on physical layout.
http://farrago.sourceforge.net/design/CollectionTypes.html
However, good luck finding a database engine that necessarily supports such features. Some support array types, but I haven't seen too many that support multisets.
As for pervasive NULLs, isn't that more the fault of schema design?
There are a lot of things wrong with SQL. Little things like the fact that INSERT and UPDATE have different syntax for no good reason.
A few of its syntax quirks annoy me as they're nonstandard in today's languages, but it's only a shallow complaint: using '<>' for its inequality operator, and using single-quotes for strings.
I'm also disappointed in the implementations in various ways: the way Microsoft SQL Server sends query text over the wire unencrypted, in its default configuration. The way Firebird SQL has such a basic wire protocol that you can see significant performance enhancements by invoking TRIM on text-type fields. The way the optimisers are so damn primitive, especially compared to the baffling wizardry that goes on in today's (programming language) compilers.
Somewhat off topic further ranting:
But the core relational model makes good sense. I see little general value in the freeform graph-databases calling themselves 'NoSQL'. (Do we call functional programming languages "No-assignment"?)
Perhaps some of them can scale well, but can't SQL do that? Google Cloud Datastore, for instance - it can scale marvellously, but only because it imposes considerable constraints on its queries. Can't we do the same thing with an SQL subset?
I think NULL defaults are widely regarded as a bad thing by now. You should have to declare what's nullable, not declare what's not null.
> There are a lot of things wrong with SQL. Little things like the fact that INSERT and UPDATE have different syntax for no good reason.
Moreover, SELECT should be at the end not the beginning. Query comprehensions and LINQ did this right.
And yes, the implementation inconsistencies are seriously irritating as well.
> Google Cloud Datastore, for instance - it can scale marvellously, but only because it imposes considerable constraints on its queries. Can't we do the same thing with an SQL subset?
If you extend Map-Reduce with a Merge phase, then you can implement the relational algebra with joins [1]. That scales pretty well.
I'd one-up this and argue that all SQL statements should be in order of execution (within reason). Moving SELECT to the end is definitely a good start.
It's pretty much impossible to decide what an optimised query should look like on a different databases with different data.
Slow network? Fast disks? GPU optimised joins? No way to know what execution order should be, and that's a strength of the relational model.