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How can you decide when to use ORM for a database development project?

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Object-relational mapping (ORM) is a technique that allows you to interact with a database using an object-oriented programming language, such as Python, Ruby, or Java. ORM can simplify and speed up your database development process, but it also has some drawbacks and limitations. In this article, you will learn how to decide when to use ORM for a database development project, based on the following factors:

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Richard Roda

Sr. Full Stack Java Spring Database / Typescript Angular Software Developer

1 Project scope and complexity

One of the main benefits of ORM is that it abstracts the database layer and lets you focus on the business logic and user interface of your application. ORM can also help you avoid writing repetitive and error-prone SQL queries, and handle database migrations and schema changes more easily. However, ORM also introduces some overhead and performance issues, especially for large and complex projects that require fine-grained control over the database operations. ORM can also hide some of the details and nuances of the underlying database system, which can lead to unexpected results or bugs. Therefore, you should consider the scope and complexity of your project, and whether you need to optimize for development speed or database efficiency.

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Prottoy Roy

Senior Software Engineer (.NET Core Back End || API developer)
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Use orm for crud and for fetching complex data set we can use SQL .also for making db relationship we can use orm .best is to use both in same application

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2 Data model and relationships

Another factor to consider when choosing ORM is the data model and relationships of your application. ORM works best when your data model is relatively simple and consistent, and when your data entities have clear and direct relationships. ORM can also help you enforce data integrity and validation rules, and avoid data anomalies and inconsistencies. However, ORM can struggle with complex and dynamic data models, such as hierarchical, polymorphic, or many-to-many relationships. ORM can also create problems when your data model changes frequently or does not match the database schema. Therefore, you should evaluate the data model and relationships of your application, and whether they fit the ORM paradigm or require more flexibility and customization.

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Richard Roda

Sr. Full Stack Java Spring Database / Typescript Angular Software Developer
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My advice, skip the "R" of ORM. It puts you in a no-win situation. If you lazy-load the relationships, you will have the N+1 problem. If you get 1000 rows of an entity and access its relationship, you will trigger 1000 additional database loads. If you make the relationship eager, you will end up loading it in cases where you don't need it. What can you do? Use Data Transport Objects (DTOs) that contain the entities needed for a given screen or transaction. Load those entities with exactly the data needed for the job at hand. I have lost count of the number of slow / broken systems that I have fixed in my career by removing the entity relationships from the ORM layer and using DTOs instead.

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3 Database compatibility and portability

A third factor to consider when choosing ORM is the database compatibility and portability of your application. ORM can help you write database-agnostic code, which means that you can use the same code for different database systems, such as MySQL, PostgreSQL, or SQLite. ORM can also make it easier to switch between different database systems, or use multiple databases in the same application. However, ORM can also limit your access to some of the features and functionalities of specific database systems, such as stored procedures, triggers, or indexes. ORM can also generate suboptimal or inefficient SQL queries, which can affect the performance and scalability of your application. Therefore, you should assess the database compatibility and portability of your application, and whether you need to leverage the full potential of your database system or support multiple databases.

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4 Learning curve and documentation

A final factor to consider when choosing ORM is the learning curve and documentation of the ORM tool or framework that you want to use. ORM can make your database development process easier and faster, but only if you know how to use it properly and effectively. ORM can also have its own syntax, conventions, and best practices, which can differ from the native SQL language or the database system. Therefore, you should check the learning curve and documentation of the ORM tool or framework that you want to use, and whether you have enough time and resources to learn and master it. You should also look for examples, tutorials, and support from the ORM community or developers.

ORM can be a powerful and convenient technique for database development, but it also has some challenges and trade-offs. By considering the factors mentioned above, you can decide when to use ORM for a database development project, and whether it suits your needs and goals.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can you decide when to use ORM for a database development project?

1

2

3

4

5

1 Project scope and complexity

2 Data model and relationships

3 Database compatibility and portability

4 Learning curve and documentation

5 Here’s what else to consider

Database Development

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How can you decide when to use ORM for a database development project?

1

2

3

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5

1 Project scope and complexity

2 Data model and relationships

3 Database compatibility and portability

4 Learning curve and documentation

5 Here’s what else to consider

Database Development

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