Skip to main content

You are not logged in. Your edit will be placed in a queue until it is peer reviewed.

We welcome edits that make the post easier to understand and more valuable for readers. Because community members review edits, please try to make the post substantially better than how you found it, for example, by fixing grammar or adding additional resources and hyperlinks.

Required fields*

10
  • 59
    @dudelgrincen it's a paradigm shift from normalization and relational databases. The goal of a NoSQL is to read and write from the database very quickly. With BigData you're going to have scads of application and front end servers with lower numbers on DBs. You're expected to do millions of transactions a second. Offload the heavy lifting from the database and put it onto the application level. If you need deep analysis, you run an integration job that puts your data into an OLAP database. You shouldn't be getting many deep queries from your OLTP dbs anyway. Commented Nov 4, 2013 at 1:53
  • 20
    @dudelgrincen I should also say that it's not for every project or design. If you have something that works in a SQL type database why change it? If you can't massage your schema to work with noSQL, then don't. Commented Nov 12, 2013 at 0:30
  • 9
    Migrations and a constantly evolving schemas are also a lot easier to manage on a NoSQL system. Commented May 6, 2014 at 20:09
  • 23
    What if the user has 3.540 posts in the website, and he does change his username in profile? Should every post be updated with the new username? Commented Mar 2, 2016 at 17:39
  • 7
    @IvoPereira Yes and that's exactly why one should avoid modeling data this way. There is an article that explains the same scenario and its consequences: Why You Should Never Use MongoDB Commented Nov 30, 2017 at 20:43