An Outer Join is a type of database join (commonly used in SQL) that returns records from one or both tables even if there’s no matching record in the other table.
LEFT OUTER JOIN (or simply: LEFT JOIN):
→ Returns all records from the left table, and the matching ones from the right table.
→ If there’s no match, the result is filled with NULL
values from the right table.
RIGHT OUTER JOIN (or: RIGHT JOIN):
→ Returns all records from the right table, and the matching ones from the left table.
→ If there’s no match, NULL
is used for the left side.
FULL OUTER JOIN:
→ Returns all records from both tables, with NULL
where no match exists on either side.
Suppose you have two tables:
Customers
CustomerID | Name |
1 | Anna |
2 | Bernd |
3 | Clara |
Orders
OrderID | CustomerID | Product |
101 | 2 | Book |
102 | 4 | Lamp |
CustomerID | Name | OrderID | Product |
---|---|---|---|
1 | Anna | NULL | NULL |
2 | Bernd | 101 | Book |
3 | Clara | NULL | NULL |
DQL stands for Data Query Language, and it's a subset of SQL (Structured Query Language). It is used specifically to query data from a database without modifying it.
Read-only: DQL is used to retrieve data, not to insert, update, or delete it.
The primary command used is:
SELECT
Example:
SELECT name, birthdate FROM customers WHERE city = 'Berlin';
This command retrieves the names and birthdates of all customers living in Berlin — without changing any data.
Sub-language | Meaning | Main Purpose |
---|---|---|
DQL | Data Query Language | Reading data |
DML | Data Manipulation Language | Inserting, updating, deleting data (INSERT , UPDATE , DELETE ) |
DDL | Data Definition Language | Defining database structure (CREATE , ALTER , DROP ) |
DCL | Data Control Language | Managing access rights (GRANT , REVOKE ) |
TCL | Transaction Control Language | Handling transactions (COMMIT , ROLLBACK ) |
MariaDB is a relational database management system (RDBMS) developed as an open-source alternative to MySQL. It was created in 2009 by the original MySQL developers after MySQL was acquired by Oracle. The goal was to provide a fully open, compatible version of MySQL that remains independent.
MySQL Compatibility:
Enhanced Features:
Active Development:
MariaDB is a powerful and flexible database solution, highly valued for its openness, security, and compatibility with MySQL. It is an excellent choice for developers and organizations looking for a reliable open-source database.
An object-oriented database management system (OODBMS) is a type of database system that combines the principles of object-oriented programming (OOP) with the functionality of a database. It allows data to be stored, retrieved, and managed as objects, similar to how they are defined in object-oriented programming languages like Java, Python, or C++.
Object Model:
Classes and Inheritance:
Encapsulation:
Persistence:
Object Identity (OID):
Complex Data Types:
Object-oriented databases are particularly useful for managing complex, hierarchical, or nested data structures commonly found in modern software applications.
A Character Large Object (CLOB) is a data type used in database systems to store large amounts of text data. The term stands for "Character Large Object." CLOBs are particularly suitable for storing texts like documents, HTML content, or other extensive strings that exceed the storage capacity of standard text fields.
TEXT
types, which function similarly to CLOBs.TEXT
or specialized data types.
A Nested Set is a data structure used to store hierarchical data, such as tree structures (e.g., organizational hierarchies, category trees), in a flat, relational database table. This method provides an efficient way to store hierarchies and optimize queries that involve entire subtrees.
Left and Right Values: Each node in the hierarchy is represented by two values: the left (lft) and the right (rgt) value. These values determine the node's position in the tree.
Representing Hierarchies: The left and right values of a node encompass the values of all its children. A node is a parent of another node if its values lie within the range of that node's values.
Consider a simple example of a hierarchical structure:
1. Home
1.1. About
1.2. Products
1.2.1. Laptops
1.2.2. Smartphones
1.3. Contact
This structure can be stored as a Nested Set as follows:
ID | Name | lft | rgt |
1 | Home | 1 | 12 |
2 | About | 2 | 3 |
3 | Products | 4 | 9 |
4 | Laptops | 5 | 6 |
5 | Smartphones | 7 | 8 |
6 | Contact | 10 | 11 |
Finding All Children of a Node: To find all children of a node, you can use the following SQL query:
SELECT * FROM nested_set WHERE lft BETWEEN parent_lft AND parent_rgt;
Example: To find all children of the "Products" node, you would use:
SELECT * FROM nested_set WHERE lft BETWEEN 4 AND 9;
Finding the Path to a Node: To find the path to a specific node, you can use this query:
SELECT * FROM nested_set WHERE lft < node_lft AND rgt > node_rgt ORDER BY lft;
Example: To find the path to the "Smartphones" node, you would use:
SELECT * FROM nested_set WHERE lft < 7 AND rgt > 8 ORDER BY lft;
The Nested Set Model is particularly useful in scenarios where data is hierarchically structured, and frequent queries are performed on subtrees or the entire hierarchy.
A database is a structured collection of data stored and managed electronically. It is used to efficiently organize, store, retrieve, and process information. In a database, data is organized into tables or records, with each record containing information about a specific object, event, or topic.
Databases play a central role in information processing and management in businesses, organizations, and many aspects of daily life. They provide a means to store and retrieve large amounts of data efficiently and allow for the execution of complex queries to extract specific information.
There are different types of databases, including relational databases, NoSQL databases, object-oriented databases, and more. Each type of database has its own characteristics and use cases, depending on the requirements of the specific project or application.
Relational databases are one of the most common types of databases and use tables to organize data into rows and columns. They use SQL (Structured Query Language) as a query language to retrieve, update, and manage data. Well-known relational database management systems (RDBMS) include MySQL, Oracle, SQL Server, and PostgreSQL.
NoSQL databases, on the other hand, are more flexible and can store unstructured or semi-structured data, making them better suited for specific applications, such as Big Data or real-time web applications.
In summary, a database is a central tool in modern data processing, playing a vital role in storing, organizing, and managing information in digital form.
Data integrity refers to the accuracy, consistency, and reliability of data in an information system, especially in a database. It ensures that data is correct and dependable, meeting the expected standards. Data integrity encompasses various aspects:
Uniqueness: Data integrity ensures that records in a database are unique and free from duplicates, often achieved through the use of primary keys, which guarantee each record has a unique identifier.
Completeness: Complete data integrity ensures that all necessary data is present in a database, with no missing values or empty fields.
Accuracy: Data must be correct and precise, reflecting real-world conditions or actual facts accurately.
Consistency: Data integrity ensures that data is consistent and does not contain conflicting information. Data related across different parts of the system or in different tables should be in harmony.
Integrity Rules: Databases can use integrity rules to enforce that entered data meets required criteria. For example, integrity rules can mandate that a specific date field contains a valid date.
Security: Data integrity also involves protection against unauthorized alterations or deletions of data. Security measures, such as permissions and access controls, are implemented to safeguard data from unauthorized access.
Maintaining data integrity is crucial for the reliable operation of information systems and databases as it ensures that the stored data is trustworthy and meaningful. Data integrity is a central concept in database management and data management in general.