SQL vs NoSQL

There are two main types of databases in database technology that are SQL and NoSQL database. In this article, we’ll explore how these databases make different, and how each type structures the data hold so you can easily determine which type is right for you. So, let's start -

SQL

Structured Query Language (SQL) is a language that used to design relational database architects. In an SQL database like MySQL, Sybase, Oracle, or IBM DM2 - SQL executes queries, retrieves data, and edits data by updating, deleting, or creating new records. It's a lightweight, declarative language that does a lot of heavy lifting for the relational database, acting like a database’s version of a server-side script. SQL databases remain popular because they fit naturally into many venerable software stacks, including LAMP and Ruby-based stacks. These databases are well understood and widely supported, which can be a major advantage if you run into problems.

NoSQL

NoSQL databases are document-oriented. This way, unstructured data such as articles, photos, social media data, videos, or content within a blog post can be stored in a single document that can be easily found but isn’t necessarily categorized into the fields. This databases offer major advantage, particularly to app developers, is ease of access. This databases have a fraught relationship with applications written in object-oriented programming languages like Java, PHP, and Python. NoSQL databases are often able to sidestep this problem through APIs, which allow developers to execute queries without having to understand the underlying architecture of their database system.

After the overview of SQL and NoSQL, now let's find out the differences between SQL and NoSQL.

• SQL is a row-oriented database. In contrast, NoSQL is column-oriented databases.

• SQL databases are table based databases whereas NoSQL databases are document based, key-value pairs, graph databases or wide-column stores.

• SQL databases uses for defining and manipulating the data, which is very powerful. In NoSQL database, queries are focused on collection of documents. Sometimes it is also called as UnQL (Unstructured Query Language). The syntax of using UnQL varies from database to database.

• SQL databases have predefined schema whereas NoSQL databases have dynamic schema for unstructured data.

• SQL databases emphasizes ACID properties (Atomicity, Consistency, Isolation, and Durability) whereas the NoSQL database follows the Brewers CAP theorem ( Consistency, Availability and Partition tolerance ).

• SQL databases are vertically scalable. So, you can manage increasing load by increasing the CPU, RAM, SSD, etc, on a single server. Whereas the NoSQL databases are horizontally scalable. You can just add few more servers easily in your NoSQL database infrastructure to handle the large traffic.

• SQL databases are scaled by increasing the horsepower of the hardware. NoSQL databases are scaled by increasing the databases servers in the pool of resources to reduce the load.

• SQL databases are good fit for the complex query intensive environment whereas NoSQL databases are not good fit for complex queries.

• On a high-level, NoSQL doesn’t have standard interfaces to perform complex queries, and the queries themselves in NoSQL are not as powerful as SQL query language.

• SQL databases are not best fit for hierarchical data storage. On the other side, NoSQL database fits better for the hierarchical data storage as it follows the key-value pair way of storing data similar to JSON data.

• NoSQL can store data in bulk like this requires extra processing effort and more storage than highly organized SQL data. Example - Hadoop is so popular in conjunction with NoSQL database stacks, an open-source computing and data analysis platform capable of processing huge amounts of data in the cloud.

• SQL databases are best fit for heavy-duty transactional type applications, as it is more stable and promises the atomicity as well as integrity of the data. While you can use NoSQL for transactions purpose, it is still not comparable and stable enough in high load and for complex transactional applications.

• Excellent supports are available for all SQL database from their vendors. There are also lot of independent consultations who can help you with SQL database for a very large scale deployments. For some NoSQL database, you still have to rely on community support, and only limited outside experts are available for you to setup and deploy your large scale NoSQL deployments.

• SQL databases can be classified as either open-source or close-sourced from commercial vendors. NoSQL databases can be classified on the basis of way of storing data as graph databases, key-value databases, document databases, column database and XML databases.

• SQL databases are a costly affair, whereas NoSQL databases are cheaper.

• SQL database examples: MySql, Oracle, Sqlite, Postgres and MS-SQL. NoSQL database examples: MongoDB, BigTable, Redis, RavenDb, Cassandra, Hbase, Neo4j and CouchDb.