How Is SQL Is Different Than NoSQL

Introduction

Most people think data is just a piece of information, but in actuality, data is a piece of information that has been organized in forms of relevant information, tables, rows, columns, and indexes. This makes it easier to retrieve any information from the data. Data in the digital world is a piece of information processed and stored by an electronic device. This information can exist in the form of text documents, images, audio, video, software programs, or any other types of data. Computing data is processed by a CPU and is stored in files and folders on a storage device, such as the hard disk.  In order to mark any information relevant and useful, we need to make it precise, as well as sort and organize it. By doing that we can represent it and interpret it easily. For this, there is a management data storage called Database Management. A database (DB) is an electronic storage system that stores a collection of data, while database management is a method to organize and sort data for accurate representation and understanding. A database is controlled by database management.

There are two types of data storage management: SQL and NoSQL. SQL is a relational database that stores data in tabular form, while NoSQL databases are in non-tabular form and store data differently than SQL does. A few popular databases are MySQL, Oracle, MS SQL Server, and Postgres SQL. These are relational databases, while MongoDB and Apache Cassandra are NoSQL DB.

SQL

SQL was initially developed by IBM. It is a language used to communicate with several relational databases. SQL commands help to store, process, analyze and manipulate databases.

Features 

  • Accessibility
    Follows the principle of tuple relational calculus and the rules of relational algebra.
     
  • Retrieving
    It is a powerful language for fast data extraction and data modification.
     
  • Versatile
    Works with DB systems from Oracle, MS Access, IBM, etc.
     
  • Less coding
    Management of database can be done without knowing lots of coding. You just need to know the implementation of SQL commands.
     
  • Architecture
    SQL is widely used as a client-server language to connect the front end with the back end.
     
  • Access of data
    When DCL commands are used, the database is protected from unauthorized access.

Types of SQL Commands

There are five commands in SQL:

DDL

Data Definition Language (DDL) is used to define the schema of the database. It includes commands like create to create an object in the database, alter to alter the schema of the database, drop to delete database objects, rename to give another name to an object, and truncate to delete everything stored in a table.

Syntax

Create CREATE TABLE tablename (column_name1 datatype(length), column_name2 datatype(length));
Alter Alter table table_name Add new_col_name data_types(size);
Drop Droptable table_name;
Rename Rename table old table_name; To new_table_name;
Turuncate Truncate table table_name;

DML

Data Manipulation Language (DML) is used for managing data stored in an existing object. It includes commands like the insert to insert data, update to modify existing data, delete to delete everything from the database, and merge to merge two or more tables.

Syntax

Insert into tablename (column_name, column_name2) Values(value1, value2);
Update UPDATE tablename SET column1=value1, column2=value2 where condition;
Delete DELETE FROM tablename WHERE condition; 

DQL

Data Query Language (DWL) is used to retrieve data stored in the database. It includes selecting to view everything in a table.

Syntax

Select SELECT * from tablename;

TCL

Transaction Control Language (TCL) is used to handle transactions, like commit to save any transaction in the database permanently, rollback to restore the database till the last committed state, and savepoint  to temporarily store transactions.

DCL

Data Control Language (DCL) includes a grant to allow a specific user to perform a specific task, and revoke to cancel all previously granted or denied permission.

Constraints in SQL

Constraints are used to specify the rules regarding records in a table.

The constraints are:

  1. Not NULL
    Restricts NULL value from being inserted into a column.
     
  2. Check
    Verifies that values in a field satisfy a condition.
     
  3. Unique
    Ensures unique values can be inserted in the field.
     
  4. Primary key
    Uniquely identifies each record in a table.
     
  5. Foreign key
    Ensures referential integrity for a record in another table.

Normalization

Organizing a record in a table is known as normalization. Normalization helps in redundancy, by making sure that no duplicate data in this storage space is saved. It boosts execution of query.

There are five types of normalization:

  1. First Normal Form (1NF)
    Removes all the duplicate columns from the record and identifies unique columns.
     
  2. Second Normal Form (2NF)
    First it has to fulfill the requirements of 1NF. Places the subsets of data in separate tables, and creates a relationship between the tables using primary keys.
     
  3. Third Normal Form (3NF)
    This should meet all requirements of 2NF. Removes columns that are not dependent on primary key constraints.
     
  4. BCNF (Boyce Code Normal Form)
    This is an advanced version of 3NF, and is stricter than 3NF. It should meet 3NF requirements. For every functional dependency, LHS should be a super key.
     
  5. Fourth Normal Form (4NF)
    Meets all requirements of 3NF and BCNF. It should not have multivalued dependencies.
     
  6. Fifth Normal Form (5NF)
    Meets all the requirements of 4NF. It should not have any join dependencies.

Advantages and Disadvantages

Due to the many advantages of SQL, it is popular and in demand. This is partially because it is a reliable and efficient language used for communicating with relational databases. SQL also has Faster Query Processing, by which a large amount of data can be retrieved rapidly and efficiently - operations are done in a fraction of a minute. No coding skills are required, as a large number of lines of code are not required for data manipulation. SQL is open-source and can be used in programs anywhere like those in PCs, servers, and laptops. It is independent of any platform (Operating System, etc.) and also is embedded with other applications. With its many advantages, SQL also has disadvantages. For example, SQL makes some users uncomfortable when dealing with a database, due to its difficult interface. The cost of some versions is expensive, and due to business rules, users can access complete control over the database. 

NOSQL

Nowadays, NoSQL databases have emerged as popular database which was initially introduced in the late 2000s. As the storage cost was decreasing rapidly the amount of data needed to be stored in a structured way and queries to process the data were increasing rapidly which increased the complexity and difficulty to manage data so, to avoid it there was the development of NoSQL allows flexibility to store huge amounts of unstructured data.

Features

Flexible Schema

Unlike SQL DB, where we need to decide and determine a schema earlier than placing records, MongoDB, by using the default, doesn’t longer require their files to have the identical schema. This flexibility enables the mapping of documents to an entity or an item. Each document can match the facts fields of the represented entity, despite the fact that the report has huge variations from different files inside the collection.

Horizontal Scaling

Horizontal scaling, also referred to as scale-out, refers to bringing on extra nodes to share the load. that is tough with relational databases because of the difficulty in spreading out associated data throughout nodes. With non-relational databases, this is made easier considering that collections are self-contained and no longer coupled relationally. This permits them to be distributed throughout nodes more genuinely, as queries do not need to “join” them collectively throughout nodes. Scaling MongoDB horizontally is executed via sharding (preferred) and replica sets. whereas, vertical scaling refers to increasing the processing energy of a single server or cluster. both relational and non-relational databases can scale up, but sooner or later, there could be a limit in phrases of most processing energy and throughput. moreover, there are improved costs with scaling as much as high-appearing hardware, as charges do now not scale linearly.

Fast Queries by data models

We can embed related information in a single structure or document with MongoDB. These schemas are generally known as "denormalized" models which take advantage of MongoDB's rich documents. Embedded records models allow programs to keep related pieces of facts inside the same database record. As a result, programs may also need to problem fewer queries and updates to complete common operations. In trendy, embedding affords higher overall performance for study operations, as well as the capability to request and retrieve associated statistics in a single database operation. Embedded information models make it possible to update associated facts in a single atomic write operation. use embedded information models if you have "contains" relationships among entities. See model One-to-One Relationships with Embedded files. you have got one-to-many relationships between entities. In these relationships, the "many" or child documents constantly seem with or are viewed within the context of the "one" or parent files.

Ease of use

Distribution of data can be replicated across multiple data centers, linearly scalable increasing the throughput of the system directly proportional to the number of nodes in the cluster. Helps to maintain a quick response time.

These databases are designed to run on cheap commodity hardware performing write operations quickly and storing data in terabytes.

Types of NOSQL DB

  • Document databases stores information in documents similar to JSON (JavaScript Object Notation) objects. Each document consists of pairs of fields and values. The values can be of various types including things like strings, numbers, Booleans, arrays, or objects.
  • Key-value databases are a simpler type of database in which each item contains keys and values.
  • Wide-column stores store information in tables, rows, and columns in dynamic form.
  • Graph databases store information in nodes and edges. Nodes typically store data like name, place, things whereas, edges store data about the relationships between the nodes.

Few Commands to access MongoDB(NOSQL)

Suppose a document file is written in JSON format

Example

{“_id”: ObjectId("R32M"), "name" : "Rahul", "age" : 32, "gender" : "male", "salary" : 32 }
{“_id”: ObjectId("A42F"), "name" : "Aruna", "age" : 42, "gender" : "female", "salary" : 36 }
{"_id": ObjectId("A21F"), "name" : "Anulekha", "age" : 21, "gender" : "female", "salary" : 41}
{"_id": ObjectId("N24F"), "name" : "Neha", "age" : 24, "gender" : "female", "salary" : 51}
{"_id": ObjectId("A29Mf"), "name" : "Abhishek", "age" : 29, "gender" : "male", "salary" : 22 }    

1. Query documents that belong to a customer name Rahul.

Command: db.customer.find( {name: "Rahul"} )
Output: {“_id”: ObjectId("R32M"), "name" : "Rahul", "age" : 32, "gender" : "male", "salary" : 32}

2. Query documents that belong to a customer older than 40.

Command: db.customer.find( {age:{$gt:40}} )
Output: {“_id”: ObjectId("A42F"), "name" : "Aruna", "age" : 42, "gender" : "female", "salary" : 36 }

3. Query documents that belong to female less than 30.

Command: db.customer.find( $and: [{gender:”female”, age: {$ltt:30}}]} )
Output: {"_id": ObjectId("A21F"), "name" : "Anulekha", "age" : 21, "gender" : "female", "salary" : 41}
{"_id": ObjectId("N24F"), "name" : "Neha", "age" : 24, "gender" : "female", "salary" : 51}


Advantages and Disadvantages

The advantages of NoSQL databases over the traditional relational databases are being schemed free, based on key-value pairs having a flexible and simple structure. Each value has a key in NoSQL. It allows developers to store serialized objects in their databases. most open-sourced NoSQL databases are inexpensive and don’t need steeply-priced licensing to run and can be run on inexpensive hardware making their deployment cost-powerful. Working with NoSQL databases the expansion of the database is very easy and cheaper than the relational databases because it’s done by horizontally scaling and distributing the load on all nodes, rather than the vertical scaling that is usually done with traditional relational database systems, that's changing the main host with a more effective one.

As we know nothing is ever perfect which means NoSQL also has a few disadvantages most NoSQL databases are not reliable on features that are supported on relational databases such as atomicity, consistency, isolation, and durability known as ACID properties which leads to the trading off consistency for performance and scalability. These are done by developers implementing their own code to add complexity to the system, limiting the number of applications that can depend on NoSQL databases for secure and reliable transactions, like banking systems. NoSQL databases consist of incompatibility with SQL queries. this means that a manual or proprietary querying language is wanted, including even more significant time and complexity.

Opinion of Future

NoSQL databases are advanced to regular sq. databases, they're greater reliable with much less cost. They take care of more information and are geared in the direction of making life styles less difficult for the developer, consequently they're utilized in larger companies like Facebook, Amazon, and Google. Seeing as these organizations which are well worth trillions of dollars are growing and using the NoSQL databases i can thoroughly say that we will be looking to use them within the future for brand new large groups. I would say that nothing is ever perfect and NoSQL databases want to work on reliability and consistency and then they could simply be the superior database control kind.

Properties SQL NoSQL
Model Relational Database Non-Relational Database
Scalability Vertical Scaling Horizontal Scaling
Type Tabular Based Key-values, Graph, Document Database
Schema Predefined Schema Dynamic Schema
Hierarchical Data Storage Not suited Suited
Properties ACID (Atomicity, Consistency, Isolation, Durability) BASE (Basically, Available, Soft state, Eventually consistency)
Query Suited for complex query Not suited for complex query
Examples MySQL, SQL Server, Postgres MongoDB, Hbase, Neo4js, Cassandra


Summary

Data in the digital world is a piece of information processed and stored by an electronic device. This information can be in the form of text documents, images, audio, video, software programs, or other types of data. In order to make any information relevant and useful, we need to make it precise, sort and organize it by that we can represent it, and interpret it easily. For this, we have management data storage called Database Management. A database (DB) is an electronic storage system that has a collection of data while database management is to organize and sorts data for good representation and understanding. The database is controlled by database management. SQL is a language used to communicate with several relational databases. SQL commands help to store, process, analyze and manipulate databases, follows the principle of tuple relational calculus and the rules of relational algebra. SQL is a language for fast data extracting and data modification, works with DB systems from Oracle, MS Access, IBM, etc. Needs less coding. SQL is widely used as a client-server language to connect the front-end with the back-end. When DCL commands are used database gets protected from unauthorized access. Have five types of commands DCL, DDL, DML, DQL, TCL.

NoSQL databases are in non-tabular form and store data differently than SQL. Its features are flexible schema unlike SQL DB, where we need to decide and determine a schema earlier than placing records, MongoDB, by using the default, doesn’t longer require their files to have the identical schema., horizontal scaling, fast queries by data models, helps to maintain a quick response time. These databases are designed to run on cheap commodity hardware performing write operations quickly and storing data in terabytes. Types of NoSQL DB are Document databases stores information in documents similar to JSON (JavaScript Object Notation) objects. Each document consists of pairs of fields and values. The values can be of various types including things like strings, numbers, Booleans, arrays, or objects. Key-value databases in which each item contains keys and values. Wide-column stores store information in tables, rows, and columns in dynamic form. Graph databases store information in nodes and edges.