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Difference Between NoSQL And SQL

In this article I describe the difference between NoSQL and SQL.

Anmol Garg Mar 25, 2016

As the name suggests, NoSQL is "Not only Sql". It means NoSQL is different to Sql.
The following are the steps to show the difference between NoSQL and Sql 
  • Types

    NoSQL database includes many different types, such as key-value stores, document databases, wide-column stores, and graph databases.

    In SQL databases manage only type, which is SQL database with minor variations.

  • Data storage Model

    Data storage model of NoSQL is based on key-value stores, which use only two columns ("key" and "value") and store all relevant data together in a single "document" in JSON, XML, or another format.

    In SQL database, data storage is individual, which record stores as rows in tables, with each column storing data about that record. It means separate data types are stored in separate tables.

  • Schemas

    In NoSQL, we don't have predefined schema. Records contents and semantics are enforced by applications.

    In SQL database, we have fixed structure and types in advance.

  • Sharing

    NoSQL database is a shared nothing architecture. In NoSQL, each server use only its own local storage and it allows storage capacity to be increased by adding more nodes.

    SQL is a shared architecture, which support relation base database management system.

  • Data Manipulation

    In NoSQL, data is manipulated through object-orientated applications.

    In SQL database, data is manipulated through a particular specific language.

  • Graph Database

    In NoSQL, graph stores database and provides index-free adjacency, meaning that every element contains a direct pointer to its adjacent element and no index lookups are necessary.

    In SQL the database requires extremely complex queries.

Advantages of NoSQL

NoSQL database does not use structured tables and a structured query language like SQL. NoSQL is used today as an umbrella term for all databases and often relate to large data sets accessed and manipulated on a Web scale. There are different advantages, which are given below:
  • Manage big data

    Facebook is a very popular commercial site, which manages millions of visitors and data. So think as a programmer, when a user logs in, they want to be able to instantly access their account. However, each user has different information. If we want to store a record for each user, something that looked like the data records at the right. Note that not every user has the same information (some users will have a username, some will only have an email address etc.), Each record has a different length and different values.

    NoSQL databases are built to allow the insertion of data without a predefined schema. That makes it easy to make significant application changes in real-time, without worrying about service interruptions, which means development is faster, code integration is more reliable, and less database administrator time is needed.

  • Key-value Database

    The NoSQL database manages to store this kind of data, create a key for each record, and then store whatever fields are available as bins, where each bin consists of a name and a value. This type of database is called a key-value store because each record has a primary key and a collection of values (bins). It is also called a row store because all of the data for a single record is stored together, in something that we can think of conceptually as a row.

  • High Scalability

    The advent of big data and the need for large-scale parallel processing to manipulate this data has led to the widespread adoption of horizontally scalable infrastructures. Some of these horizontally scaled infrastructures at Google, Amazon, Facebook, eBay, and Yahoo involve a very large number of servers. Some of these infrastructures have thousands and even hundreds of thousands of servers. In NoSQL database, automatically spreads data across servers as necessary and horizontally, meaning that to add capacity, a database administrator can simply add more commodity servers or cloud instances.

  • Column-Oriented Stores

    The column-oriented storage allows data to be stored effectively. It avoids consuming space when storing nulls by simply not storing a column when a value doesn't exist for that column. Column-oriented databases contain one extendable column of closely related data. The row-key of the first data point could be 1 and the second could be 2. Then data would be stored in a sorted ordered column-oriented store in a way that the data point with row-key 1 will be stored before a data point with row-key 2 and also that the two data points will be adjacent to each other.

  • Faster than Relation database

    The key-value database is much more suitable for the requirements of massive big data when compared to the relational model. In short, key-value data stores are much faster. NoSQL systems are flexible enough to better enable developers to use the applications in ways that meet their needs. NoSQL databases are also often faster because their data models are simpler. So finally, NoSQL databases generally process data faster than relational databases.

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