SQL vs NoSQL

There is a lot of confusion related to technology, people nowadays just become so hyped when something new comes, though it’s not bad but choosing any of them is difficult! So I’m gonna compare the two and let you decide whichever is best for you!

SQL stands for “Structured Query language ,” and NoSQL stands for “No Structured Query Language,” except for our purposes, it’s more useful to consider it as “No Structured Query language .” In general SQL databases support an upscale query language , and therefore the data is structured during a generic form to support asking a good sort of questions and be helpful for users. Many NoSQL databases have a limited query language , and therefore the data is structured to answer a limited number of questions of the user. NoSQL is quicker than SQL because it’s optimized to answer fewer questions than SQL does. It’s really that simple. There isn’t a secret sauce that creates NoSQL faster than SQL. Query performance may be a product of how closely your arrangement matches the questions being asked by the user. If the structure of the info matches the question, then the query provides the solution quickly. But when the question asked looks different from the structure of the info , transformations are applied, and rendering the solution takes a little longer than usual. NoSQL databases are often faster than SQL because the question and answer are pre-rendered or you can also call it baked-in into the info structure. So rather than querying the information with NoSQL, we are retrieving predefined answers or collections to well-known questions. The degree to which queries are baked into the info structure varies by technology. Obviously, there are many factors to think about when evaluating performance, but recognizing that performance comes at the value of query flexibility may be a good place to start out .

Now let’s talk about Scalability, SQL databases are vertically scalable, which generally means that SQL databases can increase the load on a single server by increasing things like CPU power of CPU, adding more RAM or SSD of your system itself. Now let’s talk about NoSQL databases, NoSQL is horizontally scalable. This means that you handle more traffic in NoSQL by breaking up large tables into smaller chunks, or adding a few more servers in your NoSQL database. To make it more clear, think of it like that. In SQL it’s like adding more blocks to the same building vs adding more buildings in the neighborhood. The latter can ultimately become larger and more powerful, making NoSQL databases the well-liked choice for giant or ever-changing data sets.

Now let’s talk about structure! SQL databases are table-based, NoSQL databases on the other hand are either document-based, key-value pairs, graph databases or wide-column stores based. This makes relational SQL databases a far better option for applications that need multi-row transactions – like an accounting – or for legacy systems that were built for a relational structure.

Some basic examples of SQL databases are MySQL, Oracle, PostgreSQL, and Microsoft SQL Server, etc .In  NoSQL database we have MongoDB, BigTable, Redis, RavenDB Cassandra, HBase, Neo4j and CouchDB,etc.

Conclusion

So in conclusion I would like to let you know that, the choice of the database between sql and nosql cannot be concluded on the differences between them but the project requirements. if your application features a fixed structure and doesn’t need frequent modifications, sql may be a preferable database. Conversely, if you’ve got applications where data is changing frequently and growing rapidly, like in big data analytics, nosql is the best choice for you. and remember, sql is not deceased and can never be superseded by nosql, or any other database technologies, So it’s all the technologies that are best in what they do. it is up to the architect/developer/dba to form a far better use of them counting on the situations and wishes .

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