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If that reduction can be achieved by simply replacing Mongo with Postgres... what is the point of using Mongo? Edit: on top of that, very few things that you s

by troupo 2y ago

If that reduction can be achieved by simply replacing Mongo with Postgres... what is the point of using Mongo? Edit: on top of that, very few things that you store in the DB are non-relational. So you will always end up recreating a relational database on top of any NoSQL database. So why bother when you can just go for a RDBMS from the start?

Thews 2y ago
While data can be used in a relational way, it doesn't mean that's the best for performance or storage. Important systems usually require compliance (auditing) and need things like soft deletion and versioning. Relational databases come to a crawl with that need. Sure you can implement things to make it better, but it's layers added that balloon the complexity. Most robust systems end up requiring more than one type of database. It is nice to work on projects with a limited scope where RDBMS is good enough.
- troupo 2y ago
  > and need things like soft deletion and versioning. Relational databases come to a crawl with that need. Lol. No relational database slows to a crawl on `is_deleted=true` or versioning In general so far not a single claim by NoSQL databases has been shown to be true. Except KV databases, as they have their own uses
  - Thews 2y ago
    They slow to a crawl when you have huge tables with lots of versioned data and massive indexes that can't perform maintenance in a reasonable amount of time, even with the fastest vertically scaled hardware. You run into issues partitioning the data and spreading it across processors, and spreading it across servers takes solutions that require engineering teams. There's a large amount of solutions for different kinds of data for a reason.
    - pritambaral 2y ago
      I have built "huge tables with lots of versioned data and massive indexes". This is false. I had no issues partitioning the data and spreading it across shards. On Postgres. > ... takes solutions that require engineering teams. All it took was an understanding of the data. And just one guy (me), not an "engineering team". Mongo knows only one way of sharding data. That one way may work for some use-cases, but for the vast majority of use-cases it's a Bad Idea. Postgres lets me do things in many different ways, and that's without extensions. If you don't understand your data, and you buy in to the marketing bullshit of a proprietary "solution", and you're too gullible to see through their lies, well, you're doomed to fail. This fear-mongering that you're trying to pull in favour of the pretending-to-be-a-DB that is Mongo is not going to work anymore. It's not the early 2010s.
      - Thews 2y ago
        Where did I ever say anything about Mongo? I have worked with tables on this scale. It definitely is not a walk in the park with traditional setups. https://www.timescale.com/blog/scaling-postgresql-to-petabyte-scale https://www.timescale.com/blog/scaling-postgresql-to-petabyt... Now data chunked into objects distributed around to be accessed by lots of servers, that's no sweat. I'd love to see how you handle database maintenance when your active data is over 100TB.
        troupo 2y ago
        I'd love to see a NoSQL database handling this easier than a RDBMS
        Thews 2y ago
        You mean like scylla?
    - troupo 2y ago
      > They slow to a crawl when you have huge tables Define "huge". Define "massive". For modern RDBMS that starts at volumes that can't really fit on one machine (for some definition of "one machine"). I doubt Mongo would be very happy at that scale, too. On top of that an analysis of the query plan usually shows trivially fixable bottlenecks. On top of that it also depends on how you store your versioned data (wikipedia stores gzipped diffs, and runs on PHP and MariaDB). Again, none of the claims you presented have any solid evidence in real world.

by troupo 2y ago

Thews 2y ago

While data can be used in a relational way, it doesn't mean that's the best for performance or storage. Important systems usually require compliance (auditing) and need things like soft deletion and versioning. Relational databases come to a crawl with that need. Sure you can implement things to make it better, but it's layers added that balloon the complexity. Most robust systems end up requiring more than one type of database. It is nice to work on projects with a limited scope where RDBMS is good enough.

troupo 2y ago
> and need things like soft deletion and versioning. Relational databases come to a crawl with that need. Lol. No relational database slows to a crawl on `is_deleted=true` or versioning In general so far not a single claim by NoSQL databases has been shown to be true. Except KV databases, as they have their own uses
- Thews 2y ago
  They slow to a crawl when you have huge tables with lots of versioned data and massive indexes that can't perform maintenance in a reasonable amount of time, even with the fastest vertically scaled hardware. You run into issues partitioning the data and spreading it across processors, and spreading it across servers takes solutions that require engineering teams. There's a large amount of solutions for different kinds of data for a reason.
  - pritambaral 2y ago
    I have built "huge tables with lots of versioned data and massive indexes". This is false. I had no issues partitioning the data and spreading it across shards. On Postgres. > ... takes solutions that require engineering teams. All it took was an understanding of the data. And just one guy (me), not an "engineering team". Mongo knows only one way of sharding data. That one way may work for some use-cases, but for the vast majority of use-cases it's a Bad Idea. Postgres lets me do things in many different ways, and that's without extensions. If you don't understand your data, and you buy in to the marketing bullshit of a proprietary "solution", and you're too gullible to see through their lies, well, you're doomed to fail. This fear-mongering that you're trying to pull in favour of the pretending-to-be-a-DB that is Mongo is not going to work anymore. It's not the early 2010s.
    - Thews 2y ago
      Where did I ever say anything about Mongo? I have worked with tables on this scale. It definitely is not a walk in the park with traditional setups. https://www.timescale.com/blog/scaling-postgresql-to-petabyte-scale https://www.timescale.com/blog/scaling-postgresql-to-petabyt... Now data chunked into objects distributed around to be accessed by lots of servers, that's no sweat. I'd love to see how you handle database maintenance when your active data is over 100TB.
      - troupo 2y ago
        I'd love to see a NoSQL database handling this easier than a RDBMS
        Thews 2y ago
        You mean like scylla?
  - troupo 2y ago
    > They slow to a crawl when you have huge tables Define "huge". Define "massive". For modern RDBMS that starts at volumes that can't really fit on one machine (for some definition of "one machine"). I doubt Mongo would be very happy at that scale, too. On top of that an analysis of the query plan usually shows trivially fixable bottlenecks. On top of that it also depends on how you store your versioned data (wikipedia stores gzipped diffs, and runs on PHP and MariaDB). Again, none of the claims you presented have any solid evidence in real world.