Understanding ORM: A Comprehensive Guide to Object Relational Mapping

Introduction

Object Relational Mapping (ORM) is a revolutionary technique that bridges the gap between Object Oriented Programming(OOP) and Relational Databases(RDBMS).

Why we use ORM?

Since most modern programming relies on Object-Oriented Programming (OOP), developers primarily work with the Object Model, which organizes data as interconnected graphs of objects. On the other hand, relational databases (RDBMS) use the Relational Model, where data is stored in a tabular format with rows and columns.

This fundamental difference between the two models creates a significant mismatch. While object-oriented languages prioritize relationships and behaviors, relational databases are designed for structured, tabular data storage. Bridging this gap can be challenging.

This is where Object Relational Mapping (ORM) becomes essential. ORM acts as a middleware, seamlessly translating data between the Object Model and the Relational Model. It ensures that developers can work with objects in their code without worrying about the underlying database structure, simplifying development and reducing potential errors.

Getting Started

Based on the discussion above, you should now have a solid understanding of what ORM is and why it plays a crucial role in bridging the gap between object-oriented programming and relational databases. Let’s dive deeper into the concept of ORM, explore how it works, and uncover its key features and tools. 

How ORM Works?

The core concept of ORM is encapsulating database interactions within objects. Each ORM object comprises two key components:

1. Data: Stores the object’s properties.
2. Functionality: Handles database operations such as saving, updating, and deleting records.

The ORM engine takes care of the translation between the object model and the relational database.

What is an ORM Tool?

An ORM tool is simply a software designed to help OOP developers to interact with relational databases. It simplifies the interaction between Object Oriented Programming (OOP) and Relational Databases (RDBMS) by automating data conversion. Developers can work with objects in their code while the ORM deals with database querying process.

Popular ORM Tools by Programming Language

Java

1. Hibernate: Supports OOP features like inheritance and polymorphism, making it scalable and high-performing.
   
   
2. Apache OpenJPA: A standalone POJO persistence tool.
   
   
3. EclipseLink: An open-source solution for relational, XML, and database web services.
   
   
4. jOOQ: Generates Java code and enables type-safe SQL query building.
   
   
5. Oracle TopLink: Ideal for transforming data into relational or XML formats.

Python

1. Django: Streamlines rapid web application development.
   
   
2. web2py: A secure, scalable full-stack framework.
   
   
3. SQLObject: Provides a straightforward object interface to databases.
   
   
4. SQLAlchemy: Offers robust persistence patterns for efficient database access.

PHP

1. Laravel: Features Eloquent, an intuitive ORM for database interaction.
   
   
2. CakePHP: Provides repositories for data collections and entities for individual records.
   
   
3. Qcodo: Simplifies database interaction via terminal commands.
   
   
4. RedBeanPHP: A zero-configuration ORM tool.

.NET

1. Entity Framework: Supports multiple databases, including SQL, MySQL, and PostgreSQL.
   
   
2. NHibernate: Comes with plugins for faster development.
   
   
3. Dapper: A micro-ORM ideal for mapping queries to objects.
   
   
4. Base One Foundation Component Library (BFC): Facilitates networked database applications.

Hibernate vs JPA

Hibernate is an implementation of JPA (Java Persistence API), which is a standard specification. While JPA provides a framework for mapping Java objects to relational tables, Hibernate offers extended functionalities like caching, lazy loading, and advanced query capabilities.

Use Cases of ORM

Simplifying CRUD operations in applications.

Building secure applications with minimal risk of SQL injection.

Enhancing team productivity through faster development cycles.

Advantages & Disadvantages of ORM

Advantages

• Improving the development speed and reduces costs.
• Eliminates SQL injection vulnerabilities which enhance security threats.
• Minimises the need for basic SQL CRUD operations as they are coming inbuilt with ORM.

Disadvantages

• ORM could be slower than native SQL for complex queries as it do some internal process such as data binding etc.
• It may take some time for beginners to familiar with ORM (Steep learning curve).
• Limited performance optimisation in highly specific scenarios.

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