SQL Tutorial

• SQL | Datatypes
• SQL | DDL, DML, TCL and DCL
• SQL | TRANSACTIONS
• SQL | VIEWS
• SQL | Comments
• SQL | Constraints
• SQL | Creating Roles
• SQL | Indexes
• SQL | SEQUENCES
• SQL | Query Processing
• CTE in SQL
• SQL Trigger | Student Database
• Book Management Database
• Introduction to NoSQL

SQL Clauses / Operators

• SQL | WITH clause
• SQL | With Ties Clause
• SQL | Arithmetic Operators
• SQL | Wildcard operators
• SQL | Intersect & Except clause
• SQL | USING Clause
• SQL | MERGE Statement
• MERGE Statement in SQL Explained
• SQL | DDL, DML, DCL and TCL Commands
• SQL | CREATE DOMAIN
• SQL | DESCRIBE Statement
• SQL | Case Statement
• SQL | UNIQUE Constraint
• SQL | Create Table Extension
• SQL | ALTER (RENAME)
• SQL | ALTER (ADD, DROP, MODIFY)
• SQL | LIMIT Clause
• SQL | INSERT IGNORE Statement
• SQL | LIKE
• SQL | SOME
• SQL | OFFSET-FETCH Clause
• SQL | Except Clause
• Combining aggregate and non-aggregate values in SQL using Joins and Over clause
• SQL | ALL and ANY
• SQL | EXISTS
• SQL | GROUP BY
• SQL | Union Clause
• SQL | Aliases
• SQL | ORDER BY
• SQL | SELECT TOP Clause
• SQL | UPDATE Statement
• SQL | DELETE Statement
• SQL | INSERT INTO Statement
• SQL | AND and OR operators
• SQL | WHERE Clause
• SQL | Distinct Clause
• SQL | SELECT Query
• SQL | DROP, TRUNCATE
• SQL | CREATE
• SQL | Join (Cartesian Join & Self Join)
• SQL | Alternative Quote Operator
• SQL | Concatenation Operator
• SQL | MINUS Operator
• SQL | DIVISION
• SQL | NOT Operator
• SQL | BETWEEN & IN Operator
• SQL | Join (Inner, Left, Right and Full Joins)
• SQL | CHECK Constraint

SQL-Injection

• SQL Injection
• How to use SQLMAP to test a website for SQL Injection vulnerability
• Mitigation of SQL Injection Attack using Prepared Statements (Parameterized Queries)
• Basic SQL Injection and Mitigation with Example

SQL Functions

• SQL | Mathematical functions (SQRT, PI, SQUARE, ROUND, CEILING & FLOOR)
• SQL | Conversion Function
• SQL general functions | NVL, NVL2, DECODE, COALESCE, NULLIF, LNNVL and NANVL
• SQL | Conditional Expressions
• SQL | Character Functions with Examples
• SQL | LISTAGG
• SQL | Aggregate functions
• SQL | Functions (Aggregate and Scalar Functions)
• SQL | Date functions
• SQL | NULL
• SQL | Numeric Functions
• SQL | String functions
• SQL | Advanced Functions

SQL Queries

• SQL | Joining three or more tables
• SQL | How to Get the names of the table
• SQL | Sub queries in From Clause
• SQL | Correlated Subqueries
• SQL | Top-N Queries
• SQL | SUB Queries
• SQL | How to print duplicate rows in a table?
• SQL | How to find Nth highest salary from a table
• DBMS | Nested Queries in SQL
• SQL query to find second highest salary?

PL/SQL

• PL/SQL Introduction
• Cursors in PL/SQL
• Sum Of Two Numbers in PL/SQL
• Reverse a number in PL/SQL
• Factorial of a number in PL/SQL
• Print Patterns in PL/SQL
• Decision Making in PL/SQL
• Oracle SQL | Pseudocolumn
• SQL | Procedures in PL/SQL
• Print different star patterns in SQL
• GCD of two numbers in PL/SQL
• Centered triangular number in PL/SQL
• Floyd’s triangle in PL/SQL
• Convert distance from km to meters and centimeters in PL/SQL
• Convert the given numbers into words in Pl/SQL
• Sum of digits of a number in PL/ SQL
• Sum of digits equal to a given number in PL/SQL
• Sum and average of three numbers in PL/SQL
• Check whether a string is palindrome or not in PL/SQL
• Count odd and even digits in a number in PL/SQL
• No. of vowels and consonants in a given string in PL/SQL
• Area and Perimeter of a circle in PL/SQL
• Finding sum of first n natural numbers in PL/SQL
• Area and Perimeter of Rectangle in PL/SQL
• Sum of the first and last digit of a number in PL/SQL
• Count no. of characters and words in a string in PL/SQL
• Greatest number among three given numbers in PL/SQL
• Concatenation of strings in PL/SQL
• PL/SQL | User Input

MySQL

• MySQL | Regular expressions(Regexp)
• MySQL | Grant/Revoke Privileges
• MySQL | DATABASE() and CURRENT_USER() Functions
• MySQL | BIN() Function
• MySQL | IFNULL
• MySQL | LAST_DAY() Function
• MySQL | RENAME USER
• MySQL | DROP USER
• MySQL | CREATE USER Statement
• MySQL | Change User Password
• PHP | MySQL WHERE Clause
• PHP | MySQL ORDER BY Clause
• PHP | MySQL UPDATE Query
• PHP | MySQL Delete Query
• PHP | MySQL LIMIT Clause
• PHP | MySQL Select Query
• PHP | Inserting into MySQL database
• PHP | MySQL ( Creating Table )
• PHP | MySQL ( Creating Database )

SQL Server

• SQL SERVER | Conditional Statements
• SQL Server Identity
• SQL Server | STUFF() Function

Misc

• SQL using Python
• SQL using Python and SQLite
• SQL using Python (Handling large data)
• Check if Table, View, Trigger, etc present in Oracle
• Performing Database Operations in Java | SQL CREATE, INSERT, UPDATE, DELETE and SELECT
• Difference between Simple and Complex View in SQL
• Difference between Static and Dynamic SQL
• Having Vs Where Clause?
• Inner Join Vs Outer Join
• Difference between SQL and NoSQL

Introduction to NoSQL

NoSQL databases, as the name suggests, are databases that don't rely solely on the traditional tabular relational database management system (RDBMS) model, such as those followed by SQL databases like MySQL, PostgreSQL, and Oracle. The term "NoSQL" stands for "Not Only SQL," emphasizing that while they might support SQL-like query languages, they're not bound by the relational model.

Why NoSQL?

The rise of NoSQL databases came about due to the limitations of traditional relational databases in handling:

1. Scale: As web applications began to serve millions of users and required massive scalability, traditional RDBMS solutions often ran into performance and scalability issues.
2. Schema Flexibility: Modern applications often require more flexibility as they evolve, which is hard with the fixed schema in RDBMS.
3. Diverse Data Types: The need to handle diverse types of data, such as hierarchical, graph-based, or document-oriented data, which doesn't fit neatly into tables.

Types of NoSQL Databases

1. Document-based (Document Stores):

   • Stores data in documents, typically JSON-like.
   • Examples: MongoDB, CouchDB, RavenDB.

2. Key-Value Stores:

   • Simple hash table where a unique key corresponds to a value.
   • Examples: Redis, Riak, DynamoDB.

3. Column-based (Column Stores):

   • Designed to store and manage data in columns rather than rows.
   • Examples: Apache Cassandra, HBase.

4. Graph-based (Graph Stores):

   • Designed for data whose relations are well represented as a graph and has elements interconnected with an undetermined number of relations between them.
   • Examples: Neo4j, OrientDB, ArangoDB.

5. Object Stores:

   • Used for storing complex data and relationships in an object-oriented manner.
   • Examples: ObjectDB, ZopeDB.

Advantages of NoSQL:

1. Scalability: Designed for easy and cost-effective horizontal scaling.
2. Flexibility: Allows developers to add data on the fly, without having to first define its structure.
3. Performance: Some NoSQL databases can be tuned for specific types of applications, giving better performance.
4. Diverse Data Models: Allows modeling of data in ways more aligned with the application's needs, such as graph-based or document-based.

Limitations of NoSQL:

1. Maturity: RDBMS systems are more mature and offer more functionalities out-of-the-box.
2. Standardization: NoSQL databases lack a standardized language like SQL. Each NoSQL database can have its query mechanism and syntax.
3. Consistency: Some NoSQL databases use eventual consistency, which means they may return outdated data for some time.

When to Use NoSQL?

1. Big Data Applications: When data volume, velocity, or variety becomes a challenge.
2. Real-time Applications: Like gaming, ad targeting, and social networks.
3. Content Management and Catalogs: Where schema flexibility is beneficial.
4. Graph-based Applications: For recommendation engines, fraud detection, etc.

Conclusion:

NoSQL databases offer alternative models to the traditional RDBMS. The best choice between NoSQL and RDBMS depends on the specific needs and context of the application. In the modern landscape, it's not uncommon for organizations to use a mix of both NoSQL and RDBMS solutions to meet various data needs.