#MYSQL VS SQL VS ORACLE UPDATE#

MySQL has a few 'quirks' to how it manages things like multiple databases, which may lead you to making less good decisions if you tried to take your experience over to different DBMS, especially in bigger enterprise roles. SQLite's simplicity actually avoids most of these experiences, which is not helpful to you if that is what you hope to learn. If your aim is actually to have a bit of 'operational' experience, in terms of things like what command line tools might be available as standard for the DBMS, understanding how the DBMS handles multiple databases, when to use multiple schemas vs multiple databases, some basic privilege management etc. As others have said, SQLite would offer you the ability to very easily get started, and would give you a reasonably standard (if a little basic) SQL dialect to work with. If your aim is to have experience with SQL and any related libraries and frameworks for your language of choice (python, I think?), then it kind of doesn't matter too much which you pick so much. See moreĪ question you might want to think about is 'What kind of experience do I want to gain, by using a DBMS?'. PostgreSQL offers decent (if more complex) scalablity and redundancy solutions, and is honestly very well proven and plenty of documentation exists on optimising queries.

While these things can all be implemented in MongoDB, you tend to lose some of the convenience of ACID or have to deal with things like eventual consistency, which requires more thinking on the part of your engineers. Partitioning and window functions will be great for your own use internally too, like answering questions of 'What types of takeways perform the best for us, Italian, Mexican?' or in combination with PostGIS, answering questions like 'What kind of takeways do we need to market to, to improve our selection?'. for example will let you query for restaurants based on location, without the big cost that comes from constantly using something like Google Maps API to work out which restaurants are near to someone ordering. PostgreSQL also offers you some extensions, which are just amazing for your use-case. That to me suggests PostgreSQL, which will scale quite well if you database design is okay. Then there's a whole different set of 'relations' for people ordering, like showing them past orders, which need to refer to the restaurant etc, and credit card transaction information for refunds etc. In your case, I can imagine a number of 'relations' already, which suggest a more traditional SQL solution would work well: You have restaurants, they have maybe a few menus (regular, gluten-free etc), with menu items in, which have different prices over time (25% discount on christmas food just after christmas, 50% off pizzas on wednesdays). The blog example shows up so much for DBMS like MongoDB, because it showcases what NoSQL / document storage is very scalable and performant in: mostly isolated documents with a few views / ways to order them and filter them. The main thing to consider around database choice, is what 'shape' the data will be in, and the kind of read/write patterns you expect of that data.

I can't speak for the NestJS vs ExpressJS discussion, but I can given a viewpoint on databases. I suspect that putting in a little bit more work up front will pay high dividends and productivity once the data is normalized.Īgain - it's largely a matter of preference but I prefer SQL almost every time. I'm sure you can imagine what the data sets would look like if you use MongoDB or Postgres. It sounds like the type of problem you need to reverse engineer.

I'm using Firestore with one of my apps and MongoDB with another app but they both use MySQL for the heavy lifting and then a document database for things like permissions, caching, etc. I'm much more experienced with MySQL than any other database and I am having a hard time getting on board with noSQL entirely because it's really hard to query complex data with relationships using noSQL.

#MYSQL VS SQL VS ORACLE UPDATE#

You're going to have a really hard time normalizing the data when you can't manipulate relationships and bulk edit with a nice update query. I see that someone else responded and recommended MongoDB but since you are doing data analytics, I highly recommend you go with SQL.

Mysql vs sql vs oracle