What are the differences between NoSQL databases and how do they differ from traditional relational databases?

There seem to be a lot of new databases like "NoSQL". Some of the popular ones are CouchDB, Cassandra, and MongoDB.

What are the differences between such databases and how do they differ from traditional relational databases? What are the advantages and disadvantages of choosing NoSQL DBs over SQL DB?

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Agreed, the question is "not better", it is "what solution or set of solutions is best for this particular situation."

NoSQL , CouchDB, MongoDB, Cassandra Solr.

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While RDBMS uses relations and joins to make data simpler in database tables     
NoSQL don't use joins for performance.
NoSQL scales freely when we talk in terms of schema and data, while its very tough to scale a RDBMS if data grows.
There are restriction in size of data in RDBMS in terms of data-types capability,  files of any size can be used in NoSQL databases.
Data integrity enforcement comes to play only in RDBMS not in NoSQL databases.
ACID is not the cup of tea for NoSQL databases but for RDBMS.
RDBMS supports complex transactions whereas NoSQL keeps mum for transactions.
NoSQL does not support constraints and validations while its the basic ingredient in RDBMS.
Data is not structured in NoSQL but is highly structured in form of tables in RDBMS.

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2) RDBMS ACID, .. Atomcity, Consistency, Isolation, Durability. No-Sql CAP (, ).

3) SQL . No-SQL -, , . -SQL , . SQL Schema free.SQL .i.e SQL, int, Float.

4) RDBMS SQL ( ) , . NoSQL . UnQL ( ). UnQL . SQL , NoSQL . NoSQL , NoSQL , SQL.

Eg..Take Social Eng. , //Music/Album..etc. , , , ..etc.Here , .., , . No-SQL , , .

{
   user_id: ObjectID("65f82bda42e7b8c76f5c1969"),
   update: [
    {
      date: ISODate("2015-09-18T10:02:47.620Z"),
      text: "Nice picture."
},
{
  date: ISODate("2015-09-17T13:14:20.789Z"),
  text: "1234@some smile symbol"
}
{
    date: ISODate("2015-09-17T12:33:02.132Z"),
    text: "...Oh my god.."
  }
 ]
}

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7) Examples for No-SQL are MangoDB, Cassandra..etc, and for SQL - MySQL, SQL Server, etc.

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Source: https://habr.com/ru/post/1776485/


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