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Leaving the following claims that you think are true: 1. There is still a lot of criticism about SQL. 2. Users use higher level languages (e.g. "ORMs") [witho

Leaving the following claims that you think are true: 1. There is still a lot of criticism about SQL. 2. Users use higher level languages (e.g. "ORMs") [without involving SQL?] 3. Its flaws don't impact all that many people. 4. It is a shame [that SQL is mostly used as a compiler target] as it needn't be that way. 5. A well designed relational calculus could avoid these abstractions that come with their own problems. To be fair, it could be that you don't know what you think about those claims, but since, as the original link points out, SQL does not have a "don't know" representation...

smaudet 2y ago
> 1. There is still a lot of criticism about SQL. And rightly so, while you can write whole programs inside it, the debugger/tooling/syntax for most if not all implementations is some mix of inferior/more arcane/legitimately worse. > 2. Users use higher level languages (e.g. "ORMs") [without involving SQL?] In certain fields (web dev in particular) with "Enterprise" development mindsets, this is often true. ORMs make it eas(y|ier) to hide your SQL. At least, until you screw something up and end up either rolling back (expensive) or writing various code snippets (often in SQL) to undo changes. So even in the most common case, no you end up writing SQL if you are doing anything non-trivial or making trivial mistakes. As an aside, this more or less lines up with my experience, any time there's an additional target (SQL, Assembly, IL, make files from cmake, visual studio projects from random build system, autotools), usually the higher level tool doesn't save me from having to debug the lower level one. It usually just gets in my way and I curse the person who was "making my life easier". Source code in a common language does an unusually good job at this, actually, its a miracle I don't usually need to bust out reversing tools or stare at processor assembly. But these are the popular, well-trodden-path tools, the fringe ones usually are not worth the trouble. ORMs are just barely worth it, IMO. > 3. Its flaws don't impact all that many people. Hard disagree - I posit most tools worth using are more complicated than the "easy" case, which is a dictionary - inputs and outputs. A "tool" usually has several dictionaries, or several relational tables. So after your third relation, it becomes very easy to miss-design queries (maybe the tooling has just got way better? But that's been my experience, at least). And then, if its affecting most tools, its affecting those people who use those tools. So I'd argue the effect is actually very common, if only underappreciated ("I upgraded my PC to be 10x faster and things are fast now!" - used to be a common refrain, that's less true each year). > 4. It is a shame [that SQL is mostly used as a compiler target] as it needn't be that way. Agreed. Although normally in ORM situations, you'll find the complex/difficult queries hard coded (with parameters of course), so it is used (as not just a compiler target?). > 5. A well designed relational calculus could avoid these abstractions that come with their own problems. Maybe? Despite complaining, I'm not a database guru, however if you've been paying attention to AI at all, graph databases seem to appear to be superior, in function and form. Relational databases are good enough for many things, but I don't think they are the form most natural for data, just what we as humans like to see as reports.
- da_chicken 2y ago
  > Despite complaining, I'm not a database guru, however if you've been paying attention to AI at all, graph databases seem to appear to be superior, in function and form. Relational databases are good enough for many things, but I don't think they are the form most natural for data, just what we as humans like to see as reports. This is the same line the NoSQL crowd trotted out 20 years ago, complete with "they don't need joins!" as one of the commonly listed pros. The issue is that AI doesn't care about data integrity and consistency the way, say, a medical records database, financial database, or similar database does. Social media is largely the same way. Who cares if a random comment, post, or vote is lost? It's not ideal, but specific facts are not that important. Meanwhile, a lot of RDBMSs do store data where every fact in every field of every row is critical. We end up right back at the same point we were at with NoSQL. These alternative data stores make sense for their special purposes, but for general-purpose data storage of objects you can define the important properties of, the RDBMS works extremely well. The RDBMS is one of the oldest and most heavily tested technologies in all of computing. It's extremely unlikely that it will end up being replaced.
  - randomdata 2y ago
    > The RDBMS is one of the oldest and most heavily tested technologies in all of computing. Im not so sure about that. Not since Postgres switched to SQL in 1995 has there even been any notable RDBMS in use. As Codd points out in the link, SQL is not relational. He literally invented the relational model, so he is kind of the authority. Maybe SQL is even better, but “R” it is not.
  - smaudet 2y ago
    > Meanwhile, a lot of RDBMSs do store data where every fact in every field of every row is critical. Excellent point, however how many applications are truly critical? I didn´t say DMBS (R or otherwise) are useless - I would probably reach for one before a graph database. However I´m debating that we should all use relational algebra instead of SQL. It probably doesn´t really matter for most cases.

smaudet 2y ago

> 1. There is still a lot of criticism about SQL. And rightly so, while you can write whole programs inside it, the debugger/tooling/syntax for most if not all implementations is some mix of inferior/more arcane/legitimately worse. > 2. Users use higher level languages (e.g. "ORMs") [without involving SQL?] In certain fields (web dev in particular) with "Enterprise" development mindsets, this is often true. ORMs make it eas(y|ier) to hide your SQL. At least, until you screw something up and end up either rolling back (expensive) or writing various code snippets (often in SQL) to undo changes. So even in the most common case, no you end up writing SQL if you are doing anything non-trivial or making trivial mistakes. As an aside, this more or less lines up with my experience, any time there's an additional target (SQL, Assembly, IL, make files from cmake, visual studio projects from random build system, autotools), usually the higher level tool doesn't save me from having to debug the lower level one. It usually just gets in my way and I curse the person who was "making my life easier". Source code in a common language does an unusually good job at this, actually, its a miracle I don't usually need to bust out reversing tools or stare at processor assembly. But these are the popular, well-trodden-path tools, the fringe ones usually are not worth the trouble. ORMs are just barely worth it, IMO. > 3. Its flaws don't impact all that many people. Hard disagree - I posit most tools worth using are more complicated than the "easy" case, which is a dictionary - inputs and outputs. A "tool" usually has several dictionaries, or several relational tables. So after your third relation, it becomes very easy to miss-design queries (maybe the tooling has just got way better? But that's been my experience, at least). And then, if its affecting most tools, its affecting those people who use those tools. So I'd argue the effect is actually very common, if only underappreciated ("I upgraded my PC to be 10x faster and things are fast now!" - used to be a common refrain, that's less true each year). > 4. It is a shame [that SQL is mostly used as a compiler target] as it needn't be that way. Agreed. Although normally in ORM situations, you'll find the complex/difficult queries hard coded (with parameters of course), so it is used (as not just a compiler target?). > 5. A well designed relational calculus could avoid these abstractions that come with their own problems. Maybe? Despite complaining, I'm not a database guru, however if you've been paying attention to AI at all, graph databases seem to appear to be superior, in function and form. Relational databases are good enough for many things, but I don't think they are the form most natural for data, just what we as humans like to see as reports.

da_chicken 2y ago
> Despite complaining, I'm not a database guru, however if you've been paying attention to AI at all, graph databases seem to appear to be superior, in function and form. Relational databases are good enough for many things, but I don't think they are the form most natural for data, just what we as humans like to see as reports. This is the same line the NoSQL crowd trotted out 20 years ago, complete with "they don't need joins!" as one of the commonly listed pros. The issue is that AI doesn't care about data integrity and consistency the way, say, a medical records database, financial database, or similar database does. Social media is largely the same way. Who cares if a random comment, post, or vote is lost? It's not ideal, but specific facts are not that important. Meanwhile, a lot of RDBMSs do store data where every fact in every field of every row is critical. We end up right back at the same point we were at with NoSQL. These alternative data stores make sense for their special purposes, but for general-purpose data storage of objects you can define the important properties of, the RDBMS works extremely well. The RDBMS is one of the oldest and most heavily tested technologies in all of computing. It's extremely unlikely that it will end up being replaced.
- randomdata 2y ago
  > The RDBMS is one of the oldest and most heavily tested technologies in all of computing. Im not so sure about that. Not since Postgres switched to SQL in 1995 has there even been any notable RDBMS in use. As Codd points out in the link, SQL is not relational. He literally invented the relational model, so he is kind of the authority. Maybe SQL is even better, but “R” it is not.
- smaudet 2y ago
  > Meanwhile, a lot of RDBMSs do store data where every fact in every field of every row is critical. Excellent point, however how many applications are truly critical? I didn´t say DMBS (R or otherwise) are useless - I would probably reach for one before a graph database. However I´m debating that we should all use relational algebra instead of SQL. It probably doesn´t really matter for most cases.