Comment by weberc2
7 years ago
SQL is good enough for the existing set of applications, but that's not really saying much. There are lots of other applications for which SQL is not good enough, and those applications either don't exist because an affordable alternative doesn't exist or they implement their own proprietary database (e.g., many popular BI tools). It's safe to say that your use case--using SQL to perform one-off queries--is fine; writing a program that can dynamically build (performant) SQL to access data of arbitrary schema is quite a lot harder even if you can assume a single implementation. And much of this difficulty comes down to lack of composability.
Perhaps SQL is fine if it's your interface for accessing data on a one-off basis, but if you're trying to build a complex tool on top of it (say, an analysis tool for arbitrary data), the inconsistencies and performance concerns mount. People often end up inventing their own proprietary databases to do these analyses (e.g., virtually any business intelligence tool) assuming they can afford to do so. Perhaps EdgeQL isn't the ideal alternative, but as it is SQL is not good enough for many use cases.
SQL is extremely expressive, it's almost impossible to build something that cannot be expressed in an SQL query. In most cases when people feel like SQL cannot do something it is either because the Database does not implement a part of the standard or because they are not familiar with some of the more advanced usage of SQL. Simple SELECT FROM WHERE clauses, even including JOIN, are still fairly simple compared with what you CAN do if you want.
I'd recommend reading the PGSQL manual, they go very in depth about many of the supported features and how they are implement and can be used.
"SQL is extremely expressive, it's almost impossible to build something that cannot be expressed in an SQL query."
That's kind of orthogonal to what I think is the issue being expressed here.
SQL can do many things; the problems tend to be when a query doesn't perform consistently and predictably. There's always a balance to be struck between communicating what is to be done, and how it is to be done, and SQL leaves so much of the "how" out that the query interpreter/optimizer is incredibly sophisticated and does a fantastic amount of work and yet frequently gets things spectacularly wrong, maybe due to misconfiguration and maybe due to fundamental limitations.
Obviously more information on how to do something is not always better; otherwise we'd be using assembler. But there is a balance.
Experts tend to say "write everything in one query, and if it doesn't work, fix the configuration of your database" which is not helpful given the division of responsibilities in any company. But they will say that because they are devoted to the idea that all that expressiveness is good for something.
> SQL is extremely expressive, it's almost impossible to build something that cannot be expressed in an SQL query.
If that were true, people would build RDBMS’s in SQL.
SQL isn't a general purpose language, it's a data query language.
It fulfils its purpose and does it well.
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Most of a RDBMS is actually build using SQL. (For example, in PG constraints and foreign keys are done using triggers and SQL Functions.)