Translating Objects into Relations: An Introduction to ORM

Translating Objects into Relations: An Introduction to ORM


7 min read


Definition of ORM (Object-Relational Mapping)

ORM, short for Object-Relational Mapping, is a technique used in software development to bridge the gap between the object-oriented programming paradigm and the relational database management systems. It provides a way to interact with databases using objects, rather than writing raw SQL queries or using a database-specific API.

Explanation of why ORM is important

ORM is important because it allows developers to work with databases more naturally and efficiently, by using objects and classes that they are already familiar with. It eliminates the need for developers to write raw SQL queries, which can be error-prone and difficult to maintain, especially as the database schema changes over time.

ORM also allows for a more flexible and scalable approach to data management, as it can work with multiple types of databases and can support different techniques for mapping objects to database tables. This means that an application using ORM can be easily adapted to work with different databases, without the need for major code changes.

ORM Basics

Overview of how ORM works

ORM works by providing a mapping between objects in the application code and the corresponding rows in the relational database. The ORM tool uses this mapping to automatically generate the appropriate SQL queries to create, read, update, and delete data in the database.

The ORM tool also provides a set of APIs for the developers to interact with the database using the mapped objects. These APIs typically include CRUD (Create, Read, Update, Delete) operations as well as more advanced features such as lazy loading and caching.

When a developer operates on a mapped object, such as saving or deleting it, the ORM tool converts the operation into the corresponding SQL query and executes it against the database. When data is retrieved from the database, the ORM tool maps the rows to the corresponding objects and returns them to the developer.

Comparison of ORM to traditional database management

ORM provides a significant departure from traditional database management techniques, in that it allows developers to interact with databases using objects rather than writing raw SQL queries or using a database-specific API.

Traditional database management typically involves writing SQL queries to create, read, update, and delete data in the database. This approach can be error-prone, as developers may make mistakes in the SQL syntax or forget to handle edge cases. It also requires a significant amount of boilerplate code to handle database connections, transactions, and result sets.

In contrast, ORM allows developers to work with objects that they are already familiar with, eliminating the need to write raw SQL queries. The ORM tool takes care of translating the operations on the objects into the appropriate SQL queries and executing them against the database. This abstraction layer makes the code more maintainable and easier to understand, as it eliminates the need to work with SQL and the underlying database structure.

Another major advantage of ORM is its ability to handle the relationships between different objects. With traditional database management, developers need to manually handle the JOINs and the loading and saving of related objects. ORM provides a way to handle these relationships automatically, making the code more efficient and less error-prone.

ORM Techniques

Overview of different ORM techniques (e.g. Active Record, Data Mapper)

When working with ORM, there are two main techniques used to map objects to a relational database: Active Record and Data Mapper.

Active Record is an ORM technique where each object represents a row in a database table and has methods for creating, reading, updating, and deleting the corresponding row. In Active Record, the object's state is directly mapped to the database and the object is responsible for interacting with the database. This makes it easy to work with, as the developer does not need to write explicit SQL statements, but it can lead to tight coupling between the object and the database. Examples of Active Record ORM frameworks are Ruby on Rails's ActiveRecord, Laravel Eloquent, and Django ORM.

Data Mapper is an ORM technique where there is a separation of concern between the object and the database. The object does not interact directly with the database, but instead, a Data Mapper component handles the data access and mapping between the object and the database. This allows for a more flexible and decoupled architecture, but it can make the development process more complex, as the developer needs to write explicit SQL statements. Examples of Data Mapper ORM frameworks are Doctrine, Hibernate, and MyBatis.

ORM Best Practices

Tips for designing a database schema

Designing a database schema is an important step in the development process, as it lays the foundation for the application's data storage and retrieval. Here are some tips to consider when designing a database schema:

  1. Understand the requirements: Before designing the schema, it is important to understand the specific requirements of the application. This includes understanding the data that needs to be stored, the relationships between the data, and any constraints that need to be imposed.

  2. Normalize the data: Normalization is the process of organizing data in a way that eliminates data redundancy and improves data integrity. By normalizing the data, you can ensure that the schema is efficient, easy to maintain, and less prone to errors.

  3. Define clear and consistent naming conventions: Clear and consistent naming conventions make the schema more readable and easier to understand. Use descriptive and meaningful names for tables, columns, and other schema objects.

  4. Use constraints to enforce data integrity: Constraints, such as primary keys, foreign keys, and check constraints, can be used to enforce data integrity and prevent the insertion of invalid data.

  5. Use indexes to improve query performance: Indexes can be used to improve query performance by allowing the database to quickly locate specific data. Be mindful of indexing because it can also cause performance issues when it is not used properly.

  6. Test the schema: Before implementing the schema in a production environment, it is important to test the schema thoroughly to ensure that it meets the requirements and that it performs well under load.

By following these tips, you can design a database schema that is efficient, easy to maintain, and well-suited to the specific needs of the application.

Tips for performance optimization

Performance optimization is an important aspect of database design, as it can have a significant impact on the overall performance of the application. Here are some tips to consider when optimizing the performance of a database:

  1. Understand the workload: It is important to understand the specific workload of the application to identify performance bottlenecks. This includes understanding the types of queries that are being executed, the number of concurrent users, and the volume of data that needs to be stored and retrieved.

  2. Optimize queries: Query optimization is one of the most important aspects of performance optimization. Make sure that the queries are well-written and that they make use of appropriate indexes.

  3. Use caching: Caching can significantly improve the performance of an application by reducing the number of requests that need to be made to the database.

  4. Use denormalization: Denormalization is the process of adding redundant data to the schema to improve query performance. It can be useful in situations where the cost of normalization outweighs the benefits.

  5. Monitor performance: Monitor the performance of the database regularly to identify any performance issues and to track the impact of any changes that are made.

  6. Use the right hardware: Having the right hardware to support the database is also very important. Make sure that the hardware is powerful enough to handle the workload and that it is configured appropriately.

  7. Use connection pooling: connection pooling can improve the performance of an application by reusing database connections, rather than creating a new connection each time a request is made.

By following these tips, you can optimize the performance of a database, reduce the risk of performance issues, and ensure that the application runs smoothly and efficiently.


In conclusion, ORM is a powerful technique that allows developers to work with databases in an object-oriented way, making it easier to interact with databases and eliminating the need for a deep understanding of database management. By choosing the right ORM framework or technique and designing the database schema in a way that is optimized for performance, developers can ensure that their application runs smoothly and efficiently.

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