Structured Query language (SQL)
SQL database is a domain-specific programming language used for managing, and designing data stored in a relational database management system (RDBMS). Also, it is used for stream processing in RDBMS. Relational databases use relations (typically called tables) to store data and match that particular data by using common characteristics within that dataset.
SQL often pronounced as “S-Q-L” or “See-Quel” is the standard language for dealing with Relational Databases invented in 1974 and is still going strong with their latest released version in 2016. It is particularly useful in handling structured data which is data incorporating relations among entities and variables.
A relational database defines relationships in the form of tables and SQL is effectively used to insert, search, update, delete database records.
Database
SQL database is originally based on Relational Algebra and Tuple relational calculus consisting of various types of statements. These statements can also be classified as sublanguages, called: A Data query language (DQL), Data Definition Language (DDL), a Data Control Language (DCL), and a Data Manipulation Language (DML).
Schema For SQL
A Schema in SQL is a template/ a pattern that describes qualities regarding the information a database will store.
Specifically, it describes:
Type – Type of information refers to a specific piece of information and general attributes of that particular information. For example, integers can be positive or negative and they don’t have a fractional part. This piece of information about their characteristics makes a huge difference in the way they are being efficiently stored.
Size – The size of each piece of information determines how much space it will occupy in the database. Although the price of storage has come down, still it is not practical to leave an infinite storage space. This information is recognized at the designing stage when building and maintenance of databases happen.
Organization – It refers to how the information is grouped and stored as per the user’s convenience and intended use at a particular point in time. Organization of information is stored in such a way that it is on a priority basis and unused or to be used later information is stored separately, making it a comfortable experience for the user.
SQL provides an organized and systematic approach to accessing information through various methods like:
Data query
Data manipulations (insert, update and delete),
Data definition (schema creation and modification),
Data access control
Although the SQL database is essentially a declarative language, it includes procedural elements also.
NoSql
NoSQL is a non-relational database management system, that does not require a fixed schema, avoids joins, and is easy to scale. NoSQL database is used for distributed data stores with humongous data storage needs.
NoSQL stands for “not only SQL,” or “Not SQL” an alternative to traditional relational databases where data is placed in tables and schema is carefully designed before the database is built.
A NoSQL database is self-describing, so it does not require a schema. Also, it does not enforce relations between tables in all cases. All its documents are JSON documents, which are complete entities and one can readily read and understand.
A NoSQL database system encompasses a wide range of database technologies that can store structured, semi-structured, unstructured and polymorphic data.
‘NoSQL’ refers to high-performance, non-relational databases that utilize a wide variety of data models. These databases are highly recognized for their ease-of-use, scalable performance, strong resilience, and wide availability.
Database
According to Wikipedia “A NoSQL database provides a mechanism for storage and retrieval of data that is modelled in means other than the tabular relations used in relational databases.”
For more details about SQL and NoSql:-
Top comments (3)
Feel like if you title the post "Which is best for you?" maybe you should include scenarios and explanations as to why you'd choose one over the other?
@johnathon, I like the link you shared - it provides an in-depth description of the two concepts!
Here's a take on the 'Which is best for you' question, if I was to boil it down to a few key points:
Consider SQL if:
Consider NoSQL if:
In the case you are deciding between the two and are unconvinced either way, I recommend tending toward SQL over NoSQL to avoid premature optimization. It's much easier to migrate a normalized format to a denormalized format than it is go the other way!
My heuristics is far simpler:
1) In case you know how your data and access patterns -short: you know what you are doing- NoSQL might be a good idea*
2) Otherwise: SQL should work well for you.
*But having JSON and Array Types in traditional relational databases are limiting the need for NoSQL.