You're conflating the concept of a normalized database with insanely slow DB-enforced referential integrity/foreign keys.
Toy example? Sure. Take a well-formed 3NF schema and disable foreign key constraints.
> Take a well-formed 3NF schema and disable foreign key constraints.
I'm familiar with 3NF, but can you expand on how 3NF enables you to remove foreign keys? Or feel free to point me to an article/blog, I don't want to waste your time if it's too much to explain. I did some googling but wasn't sure where to proceed from your post.
user = {user_id, email}
order = {order_id, user_id}
Enabling RDBMS-enforced foreign key constraints is the issue. It slows everything down dramatically.
How slower is it really? MySQL automically creates indexes for foreign keys so I don't think it slows down "dramatically", just an additional indexed retrieval?
Do you know of any benchmarks which show the difference?
Something like SQL Server can enforce foreign key constraints if you explicitly tell it your relationships between tables. The downside is that having this referential integrity costs you performance as the database has to check your relations when inserting/updating/deleting rows. E.g. checking that a foreign key is pointing at a valid primary key, checking that you aren't leaving invalid foreign keys when deleting a primary key, etc. This is to prevent you inserting bad data into the database.
You can delete these constraints and still have the exact same behavior so long as your code is correct. It just means that the database isn't going to stop you writing bad data.
My sense is that many typical CRUD apps aren't writing gargantuan volumes of data or making very complex edits, and if they do, it's ok if it takes a second longer. Usually read speed is more of a bottleneck for user-facing applications, but I'm sure there are probably some examples where this tradeoff is worth it.
This is a pretty tough definition of correct, though. Without foreign key constraints you'll have a really tough time dealing with concurrency artifacts without raising your isolation levels, which generally brings larger performance concerns.
My experience is that if you have a moderate amount of foreign keys, a lot of DBMS (not Postgres) will refuse the `ON DELETE CASCADE` (in the diamond case), and you have to do it "manually" anyway (from your query builder).
I’m not talking about using cascade - this applies perfectly well to use of on delete restrict. FKs are more or less the only standard way to reliably keep relationships between tables correct without raising up the isolation level (at least, in most dbs) or doing explicit locking schemes that would be slower than the implicit locking that foreign keys perform.
Table Resources: resourceid, userid, etc
If I want to restrict deletion of a user to only be possible after all the resources are deleted, I'm forced into using higher-than-default isolation levels in most DBs. This has significant performance implications. It's also much easier to make a mistake - for example, if when creating a resource I check that the user exists prior to starting the transaction, then start the tran, then do the work, it will allow insertion of data into a nonexistent user.
select id from users where id = ? for update;
if row_count() < 1 then raise 'no user' end if;
insert into sub_resource (owner, thing) values (?, ?);
commit;
??
If we take postgres as an example, performing the select takes exactly zero row level locks, and makes no guarantees at all about selected data remaining the same after you’ve read it.
edit: my mistake - I missed that the select is for update. Yes, this will take explicit locks and thus protect you from the deletion, but is slower/worse than just using foreign keys, so it won't fundamentally help you.
further edit: let's take an example even in a higher isolation level (repeatable read):
-- setup
postgres=# create table user_table(user_id int);
CREATE TABLE
postgres=# create table resources_table(resource_id int, user_id int);
CREATE TABLE
postgres=# insert into user_table values(1);
INSERT 0 1
Tran 1:
postgres=# BEGIN TRANSACTION ISOLATION LEVEL REPEATABLE READ;
BEGIN
postgres=# select * from user_table where user_id = 1;
user_id
---------
1
(1 row)
Tran 2:
postgres=# BEGIN TRANSACTION ISOLATION LEVEL REPEATABLE READ;
BEGIN
postgres=# select * from resources_table where user_id = 1;
resource_id | user_id
-------------+---------
(0 rows)
postgres=# delete from user_table where user_id = 1;
DELETE 1
postgres=# commit;
COMMIT
Tran 1:
postgres=# insert into resources_table values (1,1);
INSERT 0 1
postgres=# commit;
COMMIT
Data at the end:
postgres=# select * from resources_table;
resource_id | user_id
-------------+---------
1 | 1
(1 row)
postgres=# select * from user_table;
user_id
---------
(0 rows)
This stuff is harder than people think, and correctly indexed foreign keys really aren't a performance issue for the vast majority of applications. I strongly recommend just using them until you have a good reason not to.
On delete cascade, depending on how many rows it cascades to, can be problematic because it's a very long running blocking operation. That's something one might want to do as a background operation and in batches. Although that won't make it faster.
Personally, I find delete on cascade dangerous. I mean, lots of fun for a pen tester, sure…
Intriguing. Can you tell me more?
Sure, I meant an index in which the key is primary. But, on second thought, that's probably me misreading the GP's message.
> On delete cascade, depending on how many rows it cascades to, can be problematic because it's a very long running blocking operation. That's something one might want to do as a background operation and in batches. Although that won't make it faster.
That can definitely be a problem (just like destructor deallocation stampedes in C++ or Rust). Still less risky than cascading manually and asynchronously, I suspect.