Comparing ORM vs SQL: What To Know (2024)

November 18, 2020 | Posted by admin in Programming

When it comes to data management and storage, databases are used because they guarantee fast and easy data integrity and retrieval of information. Managing applications must include a reliable database to meet your preferences and project requirements.

However, directly dealing with databases from applications can be challenging because of the differences in data structure. Expressing subtleties of entities’ relationships also poses issues. This is why you need a tool which acts as an interface between the data layer and the core application. And the two most common tools available are SQL and ORM.

In this article, you will learn more about SQL and ORM and compare the two, so you can choose the best tool to use for your database management.

Comparing ORM vs SQL: What To Know (1)

What Is SQL?

Structured Query Language (SQL) is a language designed specifically for managing large amounts of data held in an SQL relational database management system. This type of language is commonly known as a procedural programming language.

The main purpose of this procedural programming language is to allow an administrator to have complete control over the information, which needs to be accessed from a database server. This type of language can be used to create a system capable of processing the data at various stages.

But how does SQL differ from ORM? ORM vs SQL is a good topic to discuss, but before the comparison, it is important to know how SQL works.

How SQL Works?

As the different SQL functions are performed, the results are logged in the log file. These logs are then used for tracking what the administrator is doing. The program that creates the log files is called a query engine or query language (QL) application.

These programs can be stored in a database file or on a hard drive. The administrator can view the results from one of these programs by executing a command, such as “EXEC SQL SERVER”.

What Is A Query?

A query is simply a procedure which tells the system what to do – for example, how to collect the necessary data to perform the desired function. The results from a query can be displayed in many different ways. They are typically stored in a log file, created when a query is executed.

There are several types of queries, but each one is used to retrieve the data that the system needs from the database server. The most common type of query is the Normal Query, which is used to retrieve the most basic data from the server. The other types of queries are used to retrieve data of more detailed information.

Some of the more common types of queries that can be performed on a database include:

  • Inverted Indexed Query (IJ)
  • Inverted Indexed Lookup (IILD)
  • Indexed Table Query (OT)
  • Reverse Indexed Table Query (RITQ),
  • Reverse Lookup on Table

Note: The data extracted is usually stored as a query result. The query used to retrieve the data from the database is called a Data Extractor.

What Is ORM?

Web developers use object relational mappers or ORMs to create an abstraction layer, so that they can work with databases without modifying the object-oriented paradigm, which reduces the burden of adapting to a storage format’s database specifics.

Comparing ORM vs SQL: What To Know (2)

ORM Versus SQL

Hands-On Management

When it comes to hands-on management, SQL is higher than ORM. It is because of the human expertise involved in running queries in data management and retrieval.

It is important to know how to use SQL in order to maximize the benefits and performance of the database. SQL Optimization can be done by learning the various SQL statements which are used in the database. Some of the steps involved in SQL optimization are:

  • Inserting: An SQL statement can insert data into a database. The data can be inserted into the database from a file on a file server, or an external device, such as a hard drive, an internet file share, or even a memory stick.
  • Selects: Selects are used to retrieve data from the database by different methods, such as by name, column, range or value. These include: Select Statement, Select List and Indexed Index.
  • Rows: The most common way to execute queries to retrieve rows from a database is using the Rows Query and Rows Result. The data from each row can be obtained through the Rows Statement.
  • Queries: If a database needs to retrieve data from another database, then a query can be used to do this by specifying the name of the data that is required. An example of this would be to perform an SQL query to retrieve the name of the employees in a certain department from a company database. Then, after the data has been retrieved, the query can be executed to retrieve the names of the employees by department.

Level Of Abstraction

What does the level of abstraction mean in programming? This refers to the system’s complexity when it is programmed or viewed. The higher the abstraction level is, the less detail the database contains.

The level of abstraction is higher in ORM as compared to SQL. Abstraction is one of the key principles of ORM, along with inheritance and encapsulation. All of these help to reduce complexity and increase efficiency in managing databases, by hiding the relevant data of an object.

Level Of Complexity

ORM is more complex than SQL because its high level of abstraction, and less hands-on management required. It provides programmers with a greater amount of control over how their software can be used. When a programmer uses the object-oriented programming approach, they can decide how to provide a more structured method of data access and also how to manage a database. This will allow for a more streamlined way of handling a company’s IT infrastructure, and will improve the overall usability of the software.

Conclusion

ORM and SQL are two tools available that web developers can use in database management. When comparing them, SQL has a higher hands-on management than ORM. Because ORM has a higher level of abstraction and more complexity than SQL, less hands-on management is required; this makes data management more efficient.

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Comparing ORM vs SQL: What To Know (2024)

FAQs

What is the difference between SQL and ORM? ›

Object-Relational Mapping (ORM) is a technique that allows developers to interact with a relational database using high-level object-oriented programming constructs, while raw SQL queries involve writing SQL statements directly to interact with the database.

Should I learn SQL before ORM? ›

While you don't have to learn the syntax of SQL, you still have to learn how the flow of SQL works. When using an ORM the data doesn't magically appear, you still need to understand CRUD statements and clauses. Debuging, performance tuning, and pulling out complex data can be a trial and error process.

Why raw SQL is better than ORM? ›

Performance: Raw SQL queries can be highly optimized for specific database systems and can often outperform ORM-generated queries, especially for complex operations or large datasets.

What are the advantages of employing ORM in comparison to traditional SQL based database interactions? ›

Faster development. With ORM, engineers omit writing boilerplate SQL commands and can reuse the code multiple times. As a result, they become more productive, especially at the start of the project, having more time to focus on business logic rather than on building queries. Simpler code writing and maintenance.

Which is better ORM or SQL? ›

SQL requires developers to work directly with code. That means it's often easier for them to carry out low-level troubleshooting because they can see exactly what queries got them to a certain point. ORM works with a layer between the developer and the code, so it's not easy to see what's happening in the background.

Is SQL faster than ORM? ›

In general, using raw SQL queries can be faster than using an ORM like Django's in some cases, particularly for complex queries or queries that involve large amounts of data. This is because raw SQL queries allow for more control over the query optimization process, and can often result in more efficient queries.

Why use ORM over SQL? ›

ORMs can be useful abstractions that make working with databases a lot easier. They can help you design and iterate quickly and bridge the conceptual differences between the application logic and database structures.

Why ORMs are not heavily used in go? ›

This whole example is somehow specific to JPA but it illustrates one of the major drawbacks of ORMs, which is the lack of flexibility. ORMs allow you to query your database without manipulating SQL queries but this comes with a cost. As expected, ORMs are not a prefect world.

Is 3 months enough to learn SQL? ›

At this level, it is essential to start working on real-world projects and mastering databases. This will help you practice and apply your knowledge in a practical setting. It may take around 3-6 months of consistent learning and practice to reach an intermediate level of proficiency in SQL.

What is the downside of ORM? ›

One of the drawbacks of ORM is that it 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.

Why not use an ORM? ›

There is a point where an ORM will become a hinderance. This occurs as the product scales and the number of customers grow. The poor SQL code written early by the ORM begins to degrade in performance. ORMs tend to create more code than an Engineer would writing SQL directly.

Is ORM slower than SQL? ›

Long story short: for anything but the most basic of queries, ORMs require multiple queries to fetch all the data you need. This, more than anything else, is why ORMs are perceptually slower than raw SQL.

Why is ORM preferred over JDBC? ›

JDBC: Requires more manual coding for database interactions, potentially slowing down development. ORM: Streamlines database interactions, reducing boilerplate code and accelerating development. Maintenance: JDBC: Can be more challenging to maintain due to manual management of SQL queries and transactions.

What are the pros of ORM? ›

Here are some of the advantages of using an ORM tool:
  • It speeds up development time for teams.
  • Decreases the cost of development.
  • Handles the logic required to interact with databases.
  • Improves security. ...
  • You write less code when using ORM tools than with SQL.
Oct 21, 2022

Why should we use ORM? ›

In general, ORMs serve as an abstraction layer between the application and the database. They attempt to increase developer productivity by removing the need for boilerplate code and avoiding the use of awkward techniques that might break the idioms and ergonomics that you expect from your language of choice.

Is SQL a ORM? ›

If you haven't heard of us, sqlc generates fully type-safe idiomatic code from SQL. Think of it as a reverse ORM: you write SQL queries in a text file, run sqlc generate , and then continue writing your code. It works great for Go and additional language support is on the horizon.

Does ORM use SQL? ›

This capability is particularly useful for developers who either don't know SQL or don't want to waste time writing SQL code. With ORM, they don't have to understand and write SQL or rely on SQL query builders to add an abstraction layer to the SQL code.

What does ORM stand for SQL? ›

An ORM, or Object Relational Mapper, is a piece of software designed to translate between the data representations used by databases and those used in object-oriented programming.

Is ORM more secure than SQL? ›

One of the main benefits of using an ORM framework is that it can prevent SQL injection attacks by automatically escaping or sanitizing the user input before sending it to the database. This means that any SQL commands that are inserted by malicious users are treated as strings and not executed by the database.

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