Which of the following is true of nosql databases?

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Prerequisites – SQL, NoSQL 
When it comes to choosing a database the biggest decisions is picking a relational (SQL) or non-relational (NoSQL) data structure. While both the databases are viable options still there are certain key differences between the two that users must keep in mind when making a decision. 

The Main Differences: 

1. Type – 
   SQL databases are primarily called as Relational Databases (RDBMS); whereas NoSQL database are primarily called as non-relational or distributed database. 
2. Language – 
   SQL databases defines and manipulates data based structured query language (SQL). Seeing from a side this language is extremely powerful. SQL is one of the most versatile and widely-used options available which makes it a safe choice especially for great complex queries. But from other side it can be restrictive. SQL requires you to use predefined schemas to determine the structure of your data before you work with it. Also all of your data must follow the same structure. This can require significant up-front preparation which means that a change in the structure would be both difficult and disruptive to your whole system. 

   A NoSQL database has dynamic schema for unstructured data. Data is stored in many ways which means it can be document-oriented, column-oriented, graph-based or organized as a KeyValue store. This flexibility means that documents can be created without having defined structure first. Also each document can have its own unique structure. The syntax varies from database to database, and you can add fields as you go. 

3. Scalability – 
   In almost all situations SQL databases are vertically scalable. This means that you can increase the load on a single server by increasing things like RAM, CPU or SSD. But on the other hand NoSQL databases are horizontally scalable. This means that you handle more traffic by sharding, or adding more servers in your NoSQL database. It is similar to adding more floors to the same building versus adding more buildings to the neighborhood. Thus NoSQL can ultimately become larger and more powerful, making these databases the preferred choice for large or ever-changing data sets. 
4. Structure – 
   SQL databases are table-based on the other hand NoSQL databases are either key-value pairs, document-based, graph databases or wide-column stores. This makes relational SQL databases a better option for applications that require multi-row transactions such as an accounting system or for legacy systems that were built for a relational structure. 
5. Property followed – 
   SQL databases follow ACID properties (Atomicity, Consistency, Isolation and Durability) whereas the NoSQL database follows the Brewers CAP theorem (Consistency, Availability and Partition tolerance). 
6. Support – 
   Great support is available for all SQL database from their vendors. Also a lot of independent consultations are there who can help you with SQL database for a very large scale deployments but for some NoSQL database you still have to rely on community support and only limited outside experts are available for setting up and deploying your large scale NoSQL deployments. 
    

Key highlights on SQL vs NoSQL: 

Key Differences between SQL and NoSQL

• SQL pronounced as “S-Q-L” or as “See-Quel” is primarily called RDBMS or Relational Databases, whereas NoSQL is a Non-relational or Distributed Database.
• Comparing SQL vs NoSQL databases, SQL databases are table-based databases, whereas NoSQL databases can be document-based, key-value pairs, and graph databases.
• SQL databases are vertically scalable, while NoSQL databases are horizontally scalable.
• SQL databases have a predefined schema, whereas NoSQL databases use a dynamic schema for unstructured data.
• Comparing NoSQL vs SQL performance, SQL requires specialized DB hardware for better performance while NoSQL uses commodity hardware.

What is SQL?

Structured Query language (SQL) pronounced as “S-Q-L” or sometimes as “See-Quel” is the standard language for dealing with Relational Databases. A relational database defines relationships in the form of tables.

SQL programming can be effectively used to insert, search, update, delete database records.

That doesn’t mean SQL cannot do things beyond that. It can do a lot of things including, but not limited to, optimizing and maintenance of databases.

Relational databases like MySQL Database, Oracle, Ms SQL Server, Sybase, etc. use SQL.

What is NoSQL?

NoSQL is a non-relational DMS, 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 is used for Big data and real-time web apps. For example companies like Twitter, Facebook, Google that collect terabytes of user data every single day.

NoSQL database stands for “Not Only SQL” or “Not SQL.” Though a better term would NoREL NoSQL caught on. Carl Strozz introduced the NoSQL concept in 1998.

Traditional RDBMS uses SQL syntax to store and retrieve data for further insights. Instead, a NoSQL database system encompasses a wide range of database technologies that can store structured, semi-structured, unstructured and polymorphic data.

Next, we will discuss the key diff between SQL and NoSQL.

Below is the main difference between NoSQL and SQL:

Difference between ACID vs BASE in DBMS

When use SQL?

The below image shows Stackoverflow questions for SQL vs NoSQL databases:

• SQL is the easiest language used to communicate with the RDBMS
• Analyzing behavioral related and customized sessions
• Building custom dashboards
• It allows you to store and gets data from the database quickly
• Preferred when you want to use joins and execute complex queries

When use NoSQL?

The below image shows the Google trends for NoSQL vs SQL:

NoSQL DB (mongo) Vs RDBMS DB (mysql) Google Trend

• When ACID support is not needed
• When Traditional RDBMS model is not enough
• Data which need a flexible schema
• Constraints and validations logic not required to be implemented in database
• Logging data from distributed sources
• It should be used to store temporary data like shopping carts, wish list and session data