| ▲ | n_u 4 days ago | |||||||||||||||||||||||||||||||||||||||||||
From my position MySQL pros: The MySQL docs on how the default storage engine InnoDB locks rows to support transaction isolation levels is fantastic. [1] This can help you better architect your system to avoid lock contention or understand why existing queries may be contending for locks. As far as I know Postgres does not have docs like that. MySQL uses direct I/O so it disables the OS page cache and uses its own buffer pool instead[2]. Whereas Postgres doesn't use direct I/O so the OS page cache will duplicate pages (called the "double buffering" problem). So it is harder to estimate how large of a dataset you can keep in memory in Postgres. They are working on it though [3] If you delete a row in MySQL and then insert another row, MySQL will look through the page for empty slots and insert there. This keeps your pages more compact. Postgres will always insert at the bottom of the page. If you have a workload that deletes often, Postgres will not be using the memory as efficiently because the pages are fragmented. You will have to run the VACUUM command to compact pages. [4] Vitess supports MySQL[5] and not Postgres. Vitess is a system for sharding MySQL that as I understand is much more mature than the sharding options for Postgres. Obviously this GA announcement may change that. Uber switched from MySQL to Postgres only to switch back. It's a bit old but it's worth a read. [6] Postgres pros: Postgres supports 3rd party extensions which allow you to add features like columnar storage, geo-spatial data types, vector database search, proxies etc.[7] You are more likely to find developers who have worked with Postgres.[8] Many modern distributed database offerings target Postgres compatibility rather than MySQL compatibility (YugabyteDB[9], AWS Aurora DSQL[10], pgfdb[11]). My take: I would highly recommend you read the docs on InnoDB locking then pick Postgres. [1] https://dev.mysql.com/doc/refman/8.4/en/innodb-locking.html [2] https://dev.mysql.com/doc/refman/8.4/en/memory-use.html [3] https://pganalyze.com/blog/postgres-18-async-io [4] https://www.percona.com/blog/postgresql-vacuuming-to-optimiz... [6] https://www.uber.com/blog/postgres-to-mysql-migration/ [7] https://www.tigerdata.com/blog/top-8-postgresql-extensions [8] https://survey.stackoverflow.co/2024/technology#1-databases | ||||||||||||||||||||||||||||||||||||||||||||
| ▲ | bri3d 4 days ago | parent | next [-] | |||||||||||||||||||||||||||||||||||||||||||
> I would highly recommend you read the docs on InnoDB locking then pick Postgres. This made me laugh pretty hard, but it's basically my take too. I'd pretty much go with the same thing. It's interesting to me, though, that people see Postgres as the "big database" and MySQL as the "hobby database." I basically see things as the exact opposite - Postgres is incredibly flexible, very nice to use, and these days, has fewer foot guns at small scale (IMO) than MySQL. It's more academically correct and it generally tends to "work better" at almost any achievable "normal" scale. On the other hand, Postgres is full of pitfalls and becomes very difficult at exceptionally large scale (no, not "your startup got traction" scale). Postgres also doesn't offer nearly the same quality of documentation or recipes for large scale optimization. Almost everything in the 2016 Uber article you link, which is a _great_ read, is still true to some extent with vanilla Postgres, although there are more proprietary scale-out options available now. Postgres simply has not been "hyper-scaled" to the extent that MySQL has and most massive globally sharded/replicated systems started as MySQL at some point. For this same reason, you are likely to be able to hire a MySQL-family DBA with more experience at hyper-scale than a Postgres one. With all that said, I still agree - I'd almost universally start with Postgres, with MySQL as a back-pocket scale-up-and-out option for specific very large use-cases that don't demand complex query execution or transactional workload properties. Unless you have an incredibly specific workload which is a very specific combination of heavy UPDATE and `SELECT * FROM x WHERE id=y`, Postgres will do better at any achievable scale you will find today. | ||||||||||||||||||||||||||||||||||||||||||||
| ||||||||||||||||||||||||||||||||||||||||||||
| ▲ | tracker1 4 days ago | parent | prev [-] | |||||||||||||||||||||||||||||||||||||||||||
To me, every time I've touched MySQL, I've found an issue that just rubbed me the wrong way... starting with the fact that UTF8 isn't, and even across new major versions hasn't changed to an alias for the real UTF8. (VAR)BINARY does case sensitive collation based on db default, it shouldn't do any type of textual comparison even if the data is "text". You can't do foreign keys with ANSI quotes for the table/field names... Note: some of this may have changed in the past 6+ years I've avoided looking at it again. | ||||||||||||||||||||||||||||||||||||||||||||
| ||||||||||||||||||||||||||||||||||||||||||||