How can ORM eliminate the need for manual SQL coding?

Object-Relational Mapping?(ORM) is a technique that lets you query and manipulate data from a database using an object-oriented paradigm. When talking about ORM, most people are referring to a?library?that implements the Object-Relational Mapping technique, hence the phrase "an ORM". An ORM library is a completely ordinary library written in your language of choice that encapsulates the code needed to manipulate the data, so you don't use SQL anymore; you interact directly with an object in the same language you're using.

It is true that ORM eliminates the need for manual SQL coding BUT - "I got a chance working with similar tool LINQ which generates the SQL queries on the go, but issue is that these tools can generate inefficient or suboptimal SQL queries that may result in poor performance, excessive memory usage, or unexpected errors. For example, ORM may execute multiple queries instead of a single join, or fetch more data than needed, or use inappropriate indexes or functions"

ORM eliminates manual SQL coding by providing an object-oriented interface for interacting with databases, generating SQL queries automatically based on object actions. It abstracts database specifics, allowing developers to work with different database systems seamlessly. ORM manages relationships between database entities, offers data validation, and includes performance optimizations, streamlining development and enhancing security while reducing the need for manual SQL expertise.

the ORM as a tool to build queries on the fly of the operation is perfect. but it leaves us a delta as to how optimal or efficient these are, since at the time of the implementation of an improvement for its performance (as for example a CTE) is somewhat cumbersome and sometimes the learning curve to apply the improvements suggested to a particular query is not so friendly. you can, yes .... it takes time, too ...

Imagine you have a bunch of data in a database, like a list of customers and their orders. Normally, to get that data, you'd have to write specific instructions in a language called SQL. It's like giving commands to the database to fetch the information you want. But with ORM, you don't have to write those SQL commands yourself. Instead, you work with objects in your programming language (like Java) that directly represent the data in the database. So, you interact with these objects in your code. In simpler terms, ORM acts like a translator between your code and the database, so you can focus on working with your data using familiar programming concepts, without having to worry about writing SQL queries manually.

ORM (Object-Relational Mapping) eliminates the need for manual SQL coding by providing a programming interface that allows developers to interact with the database using object-oriented concepts instead of writing raw SQL queries. ORM works by mapping database tables to classes, and rows in those tables to objects, allowing developers to perform CRUD (Create, Read, Update, Delete) operations using familiar object-oriented programming techniques. The ORM handles the translation of these object-oriented operations into the appropriate SQL queries, abstracting away the complexities of database interactions and enabling developers to focus more on application logic rather than database manipulation.

Think of the ORM as a helpful translator. You define how your objects in code correspond to tables and columns in your database. The ORM then takes care of the heavy lifting, automatically generating the necessary SQL queries based on your object manipulations. Need to create a new record? The ORM handles the "INSERT" query. Updating data? The ORM translates your object changes into an "UPDATE" query. It's like having a built-in assistant that takes care of the database communication for you.

Instead of learning the complex language of SQL, you get to talk to your database using the friendly objects you already use in your programming. This means less time spent on finicky database stuff and more time actually building your app! Example: ● Without ORM: You'd write SQL like SELECT * FROM customers WHERE city = 'New York'; to fetch customer data. ● With ORM: You might instead write something like customers = Customer.objects.filter(city='New York').

Imagine you're organizing a party with a guest list. Each guest has a name, age, and favorite drink. Normally, you'd write this in a notebook (database) using a structured format. But with ORM, you have a digital assistant who knows how to read/write in your book. Instead of searching in a notebook directly, you just tell your assistant, "Add Tom, 25, loves lemonade" Your assistant records this in the notebook. When you need to find a guest, you simply ask, "Find the guest who loves lemonade," and your assistant gives you details. Here, digital assistant is the ORM, notebook is the database, and guests are the objects in your code. ORM abstracts away the complexities of the database, allowing you to interact with your data more naturally.

An ORM simplifies database interactions by bridging the gap between relational databases and object-oriented programming languages, making it easier for developers to work with data in their applications. An ORM works by mapping database tables to classes in object-oriented programming languages. Each table in the database corresponds to a class, and each row in the table corresponds to an object (instance) of that class.

Object-Relational Mapping (ORM) provides several benefits that enhance the development process and improve the interaction between object-oriented code and relational databases. Here are some of the key advantages of using ORM: Object-Relational Mapping (ORM) provides several benefits that enhance the development process and improve the interaction between object-oriented code and relational databases. Here are some of the key advantages of using ORM: Abstraction of Database Complexity Increased Productivity Code Reusability Maintainability Portability Reduced SQL Injection Risks Simplified Database Schema Evolution Improved Readability Facilitates Object-Oriented Design Efficient Database Query Optimization

There are some cases like the need of returning aggregate results where you have to write queries manually but also mapping those manual queries on ORM will still be more advantageous compared to traditional ways of interacting with databases. One of the benefits you can get on mapping manual queries is managing page requests which is one of the mapping simplified by ORM for server side pagination handling on big data results in which ORM will provide you with sorting, limiting results per page, ordering, etc.

Los ORM proporcionan multiples beneficios. Aquí enumeraré algunos: 1. Te proporcionan un "API" de comunicación de tu backend con tu base de datos. Esto facilita mucho la legibilidad de tu código. 2. Te dan seguridad ante ataques de inyección de SQL. Aunque no hay dejarles todo el trabajo, la mayoría de los ORM respetables tienen esta capa de seguridad que realmente se agradece. 3. Facilita la migración entre motores de base de datos. Dependiendo el ORM puede ser más o menos fácil, pero la capa de Base de Datos es independiente del código, da igual si estás atacando un SQL Server, un MySQL o un MariaDB, a tu código no le interesa, con unas pocas configuraciones puedes cambiar el origen de datos.

ORM isn't just a convenience; it's a game-changer. By eliminating the need for manual SQL coding, ORM bestows a multitude of benefits upon developers. Firstly, productivity soars as developers can focus on crafting business logic instead of wrestling with SQL syntax. Secondly, portability becomes a reality—code written with ORM can effortlessly transition between different database systems without necessitating extensive rewrites. Thirdly, maintainability receives a boost as updates to code and database schemas can be seamlessly synchronized. Furthermore, ORM empowers developers to wield the expressive power of object-oriented programming, complete with features like inheritance, polymorphism, and associations, for manipulating data.

ORM simplifies database interactions by abstracting SQL queries into object-oriented operations, boosting productivity and reducing code complexity. It ensures database agnosticism, enabling seamless transitions between different systems without major modifications. Automating tasks like object-to-table mapping and query generation, ORM minimizes boilerplate code, enhancing maintainability. It streamlines transaction management, aligns with the object-oriented paradigm, and often facilitates automatic schema migration, ultimately expediting development and enhancing software quality.

ORM (Object-Relational Mapping) eliminates the need for manual SQL coding by providing a framework that allows developers to interact with a database using high-level programming constructs (such as objects, classes, and methods) rather than writing SQL queries directly. ORM libraries handle the translation of these high-level operations into SQL queries, thus abstracting away the complexities of database interactions and reducing the amount of manual SQL coding required. This abstraction simplifies database access and maintenance, promotes code reusability, and enhances productivity by allowing developers to focus more on application logic rather than database management tasks.

The Challenges are as follows Performance Overhead Learning Curve Complex Queries and Joins Inefficient Queries Vendor Lock-In Schema Management Limited Control Over Database Optimization Compatibility Issues Object-Relational Impedance Mismatch Overhead for Small Projects Caching Challenges

The ORM has a security component that should keep us alert and that is the database user used to make the connection. Usually (not to say that it is the usual practice) is the user owner of the database and database objects, and "usually" the ORM is linked to the day to day operation of the application. With this in mind, I would recommend the following : Separate the user who owns the objects and the ORM user. Isolate the user's permissions through an exclusive role (it serves as an emergency button in case of a security event). Restrict ORM user connections to those made from the container(s) associated to the application. Close the ORM user connections from any external application (Dbeaver, PGAdmin, Psql, Datadog, etc).

In my opinion, it is helpful but, the performance could be an issue! It depends on your goals to decide weather to go or not to go with it.

The challenges of ORM include potential performance overhead due to the abstraction layer between the application and the database, complexities in mapping complex object hierarchies to relational structures, steep learning curves for developers, limitations in query expressiveness compared to raw SQL, difficulties in optimizing generated queries for performance, challenges in handling concurrency and transactions efficiently, the risk of vendor lock-in, and the ongoing challenge of addressing the object-relational impedance mismatch. Despite these challenges, ORM remains a valuable tool for many developers, offering benefits in productivity, maintainability, and portability when used judiciously and with awareness of its limitations.

Here are some key factors to consider when selecting an ORM framework Programming Language and Ecosystem Database Support Performance Considerations Ease of Use and Learning Curve Flexibility and Customization Querying and Expressiveness Object-Relational Mapping Features Transaction Support and Concurrency Control Maturity and Stability Integration with Frameworks and Libraries License and Open Source Community Scalability Support and Maintenance Community Feedback Security Features

When choosing an ORM framework, consider factors like compatibility with your programming language and target database, performance overhead, feature set including CRUD operations and query language support, ease of use, flexibility for customization, documentation and community support, compatibility with existing codebase, security features, licensing and cost, vendor support and longevity, performance benchmarks, and integration with existing tools and libraries. By evaluating these factors, you can select an ORM framework that aligns with your project requirements and facilitates efficient database interactions in your application.

Quando você está escolhendo um framework ORM, há algumas coisas importantes para considerar. Certifique-se de que ele seja compatível com a linguagem de programa??o e o banco de dados que está usando. Além disso, é essencial garantir que a licen?a do ORM seja compatível com o seu projeto. O ORM pode ser uma m?o na roda porque elimina a necessidade de escrever SQL manualmente. Você pode interagir com o banco de dados usando uma linguagem de programa??o, o que simplifica o acesso aos dados. Com a estrutura ORM certa, você pode colher os benefícios de uma camada de acesso a dados simplificada, enquanto evita os possíveis problemas que podem surgir.

Understand your requirements, such as what programming language to use? What is a platform (mobile / network / PC). Easy integration with other code, how efficient it is, whether it supports transactions, what kind of documentation can be found. Performance and optimizing how it works on the platform.

Once you get beyond simple queries, ORMs typically write absolute garbage SQL. The key is knowing when to leverage an ORM vs. not. And, that decision should be managed through a database professional - not a full-stack dev. Plenty of orgs go without a database professional, because they have an ORM and full-stack devs. And it works great…until it doesn’t, and by then untangling this kind of mess costs real money (and time). “If you think it's expensive to hire a professional to do the job, wait until you hire an amateur.” -Red Adair

ORMs helps in mapping objects to database tables. They also generate SQL queries based on the operation being performed. ORMs also help with data validations. As a conclusion ORMs provide a high level of abstraction by simplifying database interactions and also automates common database operations. I have personally used Spring Data for both SQL and Non-SQL databases. They are very good but beware of the performance overload, so use ORMs carefully in your projects.

En mi opinion y experiencia un ORM es genial para sistemas transaccionales (OLTP) donde se busca almacenar y recibir cierta cantidad de datos, pero muy ineficiente para sistemas OLAP o ROLAP, en estos sistemas es mejor dejarle la tarea directamente al motor del gestor de DB, las tecnicas actuales para el manejo de grandes volumenes de datos o un servidor OLAP. pero no con un ORM.

Overall, mastering ORM frameworks and techniques adds another valuable skill to a developer's toolkit. There are often situations where we need to extend beyond our programming language expertise, and utilizing a framework that acts as a bridge between our programming language and the world of SQL and databases can significantly enhance our performance. I view it as akin to acquiring any other skill that broadens our capabilities, improves our performance, and enhances our understanding of the digital landscape.

In addition to the previously mentioned considerations, when choosing an ORM framework, it's important to assess factors like scalability, concurrency control mechanisms, error handling and logging capabilities, ORM philosophy and design patterns, maintenance overhead, performance tuning options, community and ecosystem support, vendor lock-in, testing and mocking support, and data migration capabilities. By carefully evaluating these factors alongside compatibility, performance, ease of use, security, documentation, and integration, you can select an ORM framework that best aligns with your project's requirements and facilitates efficient database interactions while ensuring long-term sustainability and extensibility.