Database triggers are special automated procedures in a database that are automatically executed when certain events occur on a table or view.
Imagine you have a table called Orders, and you want to automatically log every time an order is deleted.
You can create a DELETE trigger on the Orders table that inserts a message into a Log table whenever a row is deleted.
| Type | Description |
|---|---|
| BEFORE | Executes before the triggering action |
| AFTER | Executes after the triggering action |
| INSTEAD OF | (for views) replaces the triggering action |
CREATE TRIGGER log_delete
AFTER DELETE ON Orders
FOR EACH ROW
BEGIN
INSERT INTO Log (action, timestamp)
VALUES ('Order deleted', NOW());
END;Data validation
Audit logging
Enforcing business rules
Extending referential integrity
Can be hard to debug
Might trigger other actions unexpectedly
Can impact performance if overly complex
GitHub Actions is a feature of GitHub that lets you create automated workflows for your software projects—right inside your GitHub repository.
You can build CI/CD pipelines (Continuous Integration / Continuous Deployment), such as:
🛠️ Build your app on every push or pull request
🚀 Automatically deploy (e.g. to a server, cloud platform, or DockerHub)
📦 Create releases (e.g. zip packages or version tags)
🔄 Run scheduled tasks (cronjobs)
GitHub Actions uses workflows, defined in a YAML file inside your repository:
Typically stored as .github/workflows/ci.yml
You define events (like push, pull_request) and jobs (like build, test)
Each job consists of steps, which are shell commands or prebuilt actions
name: CI
on: [push]
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: actions/setup-node@v3
with:
node-version: '20'
- run: npm install
- run: npm testAn Action is a single reusable step in a workflow. You can use:
Prebuilt actions (e.g. actions/checkout, setup-node, upload-artifact)
Custom actions (e.g. shell scripts or Docker-based logic)
You can explore reusable actions in the GitHub Marketplace.
Saves time by automating repetitive tasks
Improves code quality through automated testing
Enables consistent, repeatable deployments
Integrated directly in GitHub—no need for external CI tools like Jenkins or Travis CI
Storyblok is a user-friendly, headless Content Management System (CMS) that helps developers and marketing teams create, manage, and publish content quickly and efficiently. It offers a visual editing interface for real-time content design and is flexible with various frameworks and platforms. Its API-first architecture allows content to be delivered to any digital platform, making it ideal for modern web and app development.
A Prepared Statement is a programming technique, especially used when working with databases, to make SQL queries more secure and efficient.
It consists of two steps:
Prepare the SQL query with placeholders
Example in SQL:
SELECT * FROM users WHERE username = ? AND password = ?
(Some languages use :username or other types of placeholders.)
Bind parameters and execute
The real values are bound later, for example:
$stmt->bind_param("ss", $username, $password);
$stmt->execute();✅ Protection against SQL injection:
User input is treated separately and safely, not directly inserted into the SQL string.
✅ Faster with repeated use:
The SQL query is parsed once by the database server and can be executed multiple times efficiently (e.g., in loops).
$conn = new mysqli("localhost", "user", "pass", "database");
$stmt = $conn->prepare("SELECT * FROM users WHERE email = ?");
$stmt->bind_param("s", $email); // "s" stands for string
$email = "example@example.com";
$stmt->execute();
$result = $stmt->get_result();A Prepared Statement separates SQL logic from user input, making it a secure (SQL Injection) and recommended practice when dealing with databases.
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 |
Transaction Control Language (TCL) is a subset of SQL used to manage transactions in a database. A transaction is a logical unit of work that may consist of one or more SQL statements—typically INSERT, UPDATE, or DELETE—that should be executed together.
TCL provides commands to ensure that transactions are properly completed or rolled back in case of errors.
| Command | Description |
|---|---|
COMMIT |
Saves all changes made in the current transaction permanently to the database. |
ROLLBACK |
Undoes all changes made since the last COMMIT. |
SAVEPOINT |
Creates a named point within a transaction that you can roll back to later. |
ROLLBACK TO SAVEPOINT |
Reverts changes back to a specific savepoint. |
SET TRANSACTION |
Defines characteristics for the current transaction (e.g., isolation level). |
BEGIN;
UPDATE account SET balance = balance - 100 WHERE account_id = 1;
UPDATE account SET balance = balance + 100 WHERE account_id = 2;
COMMIT;→ Both updates are completed together. If an error occurs, you could use ROLLBACK to cancel both operations.
TCL commands only work in database systems that support transactions (e.g., PostgreSQL, Oracle, or MySQL with InnoDB).
Data Manipulation Language (DML) is a subset of SQL (Structured Query Language) used to manage and manipulate data within a database. With DML, users can insert, query, update, and delete data — essentially everything you'd typically do with data stored in a database.
| Command | Purpose |
|---|---|
SELECT |
Retrieve data from a table |
INSERT |
Add new data |
UPDATE |
Modify existing data |
DELETE |
Remove data |
-- Insert
INSERT INTO customers (name, city) VALUES ('Müller', 'Berlin');
-- Query
SELECT * FROM customers WHERE city = 'Berlin';
-- Update
UPDATE customers SET city = 'Hamburg' WHERE name = 'Müller';
-- Delete
DELETE FROM customers WHERE name = 'Müller';DML deals with the data inside tables, not with the structure of the tables themselves (that's handled by Data Definition Language, DDL).
DML operations can often be rolled back (undone), especially when transactions are supported.
In short: DML is the toolset you use to keep your database dynamic and interactive by constantly adding, reading, modifying, or deleting data.
An Entity Manager is a core component of ORM (Object-Relational Mapping) frameworks, especially in Java (JPA – Java Persistence API), but also in other languages like PHP (Doctrine ORM).
Persisting:
Finding/Loading:
Retrieves an object by its ID or other criteria.
Example: $entityManager->find(User::class, 1);
Updating:
Tracks changes to objects and writes them to the database (usually via flush()).
Removing:
Deletes an object from the database.
Example: $entityManager->remove($user);
Managing Transactions:
Begins, commits, or rolls back transactions.
Handling Queries:
Executes custom queries, often using DQL (Doctrine Query Language) or JPQL.
The Entity Manager tracks the state of entities:
managed (being tracked),
detached (no longer tracked),
removed (marked for deletion),
new (not yet persisted).
$user = new User();
$user->setName('Max Mustermann');
$entityManager->persist($user); // Mark for saving
$entityManager->flush(); // Write to DBThe Entity Manager is the central component for working with database objects — creating, reading, updating, deleting. It abstracts SQL and provides a clean, object-oriented way to interact with your data layer.
Doctrine DBAL (Database Abstraction Layer) is a PHP library that provides an abstraction layer for database access. It is part of the Doctrine project (a popular ORM for PHP), but it can be used independently of the ORM.
Doctrine DBAL offers a unified API to interact with different databases (such as MySQL, PostgreSQL, SQLite, etc.) without writing raw SQL specific to each database system.
Easily configure and manage connections to various database systems.
Supports connection pooling, transactions, and more.
Build SQL queries programmatically using an object-oriented API:
$qb = $conn->createQueryBuilder();
$qb->select('u.id', 'u.name')
->from('users', 'u')
->where('u.age > :age')
->setParameter('age', 18);
$stmt = $qb->executeQuery();Database Independence
The same code works with different database systems (e.g., MySQL, PostgreSQL) with minimal changes.
Schema Management
Tools to create, update, and compare database schemas.
Useful for migrations and automation.
Data Type Conversion
Automatically converts data between PHP types and database-native types.
use Doctrine\DBAL\DriverManager;
$conn = DriverManager::getConnection([
'dbname' => 'test',
'user' => 'root',
'password' => '',
'host' => 'localhost',
'driver' => 'pdo_mysql',
]);
$result = $conn->fetchAllAssociative('SELECT * FROM users');You might choose DBAL without ORM if:
You want full control over your SQL.
Your project doesn't need complex object-relational mapping.
You're working with a legacy database or custom queries.
Doctrine DBAL is a powerful tool for clean, portable, and secure database access in PHP. It sits between raw PDO usage and a full-featured ORM like Doctrine ORM, making it ideal for developers who want abstraction and flexibility without the overhead of ORM logic.
A Join Point is a concept from Aspect-Oriented Programming (AOP).
A Join Point is a specific point during the execution of program code where additional behavior (called an aspect) can be inserted.
Method calls
Method executions
Field access (read/write)
Exception handling
In AOP, cross-cutting concerns (like logging, security, or transaction management) are separated from the main business logic. These concerns are applied at defined points in the program flow — the Join Points.
Pointcut: A way to specify which Join Points should be affected (e.g., "all methods starting with save").
Advice: The actual code that runs at a Join Point (e.g., "log this method call").
Aspect: A combination of Pointcut(s) and Advice(s) — the full module that implements a cross-cutting concern.
@Before("execution(* com.example.service.*.*(..))")
public void logBeforeMethod(JoinPoint joinPoint) {
System.out.println("Calling method: " + joinPoint.getSignature().getName());
}→ This logs a message before every method call in a specific package. The joinPoint.getSignature() call provides details about the actual Join Point.
Redux
