Examples of using NoSQL technologies

Question

NoSQL

Most of you have heard of new non-relational data storage technologies like MongoDB, CouchDB and others. I tried demo versions of these technologies. I basically understood the javascript-like syntax of MongoDB. Can anyone give specific situations in which the use of such DBMS is justified? The answer can be given in the form of a link to the article.

Answer 1

highscalability.com/blog/2011/6/20/35-use-cases-for-choosing-your-next-nosql-database.html - overview of NoSQL database types
rebelic.nl/engineering/the-four-categories-of- nosql-databases/?utm_source=twitter - 4 types of NoSQL database
blog.monitis.com/index.php/2011/05/22/picking-the-right-nosql-database-tool/ - and another overview

Answer 2

SQL gives built-in data structure validation through normal forms, indexes, and the like.
The data validation that SQL provides is important for development. If it does not exist, then you will have to write these checks by hand.
NoSQL makes it possible not to mess around with mapping, but to immediately save the entire data as objects to the database.
But that's not all, NoSQL solutions have the means to scale easily.
As well as the means of processing this entire large-scale economy. Specifically MapReduce .
If you have a lot of data or a lot of queries, and there is some special case on the data, then a NoSQL solution can be useful.
If not, then I quote one of the developers of Apache Hadoop. In one speech, he said: "If there is not a lot of data, then do not be shy and use plain SQL."
What to use in the final situation - see for yourself. Each option has its own advantages and disadvantages. And it would be nice to know about the shortcomings and turn them into virtues.

Answer 3

I would not talk about the justification / unjustification of this or that technology. At the moment, almost any technology can be used for a wide range of tasks. Many now put on the simplicity and clarity of the work. NoSQL is just easier to understand and work with.

Answer 4

I use both. I take the best from both solutions. nosql - speed and scalability, sql - complex queries and data transformations at the sampling stage