Python

Django vs. SQLAlchemy Comparison

As more and more technology is developed and improved over time, the number of users accessing the internet grows even more, and as a result of that, the amount of data that businesses and organizations have to deal with is growing exponentially. For a company to be successful, it needs to have tools and infrastructure that can deal with these large sets of data easily. This is exactly where the database comes into the picture which is mainly designed for the storage and collection of data. Moreover, its organized form allows users to easily manage and access the dataset. Database themselves require a management system that allows them to store and provide access to the data. Mostly, the language SQL is used to perform operations in a database, however, as your application grows and becomes more complex, it becomes extremely difficult to have an idea as to what exactly each operation is doing.

An alternative to this that was developed was the ORM (Object Relational Mapping) frameworks that actually create a bridge in connecting the database and the programming language that you prefer using in creating your application. With Python being one of the most popular programming languages this year, we shall, therefore, take a look at and compare the pros and cons of two of its most popular and widely used ORMs, Django and SQLAlchemy, in this article.

Django vs. SQLAlchemy

Both the ORMs – Django and SQLAlchemy are two of the most popular Python-based Relational Mapping tools and each one has specific, unique advantages of its own. Let us now cross-examine and look at both of their differences side-by-side.

1) Data Access Layer Implementation

Django makes use of what is called the active record implementation in which a single object instance is mapped to each row of the database and data is easily accessible from the database. Over here, it isn’t necessary to set up the schema of the database beforehand and these can easily be used by users since the main idea in Django is that it can understand the structure directly, simply by taking a look at the database schema. In addition to this, since it is a direct mapping between the database and object, any change to the object will get updated in the database as well.

SQLAlchemey uses the Data Mapper implementation that acts as the middle layer between your application and database and transfers data from between these two while keeping their connection independent of one another. This allows a far greater flexibility between the two layers as well as making use of the database in a much more efficient manner.

2) Better with Complex Queries

Both Django and SQLAlchemy are two excellent ORMs that provide some of the best features that you can find in relational mapping tools. In terms of coping and dealing with complex queries, SQLAlchemy takes the edge as it is much better at interacting with the database and as a result, it can be used to write complex queries without having to go back to raw SQL. To understand this concept let us take a look at the following queries written in both Django and SQLAlchemy.

Django:

Football.objects.filter(team__name="Manchester United")

SQLAlchemy:

SQLAlchemy: session.query(Football).join(Football, Team).filter(Team.name=="Kamma Sing")

As seen from the syntax of the two ORMs, Django appears to be more abstract in its query and only showing the established connection between the different database tables while SQLAlchemy goes into much more depth. This difference between the two shows that Django is much lazier and much more effective at dealing with complex queries.

3) Community and Databases Support

Both Django and SQLAlchemy are immensely popular relational mapping frameworks, and they’re backed by some extremely amazing communities. The latter, however, excels over this as it has a much larger community along with an absolutely stunning documentation that is testament to the fact of community members putting in their time into it. Even if you encounter any issue, you can easily post on StackOverflow or other forums and there will be a large section of people willing to aid you.

Along with this, both Django and SQLAlchemy support a large collection of databases such as MySQL, PostgreSQL, Oracle, and SQLite. For users that are already using Microsoft SQL or are planning to, then SQLAlchemy is once again the answer as MSSQL provides full support to it.

Overall, both have great communities and support a variety of databases, which is a good sign of the immense quality that each of them possesses.

4) Applications

Django was mainly designed for web applications and that is precisely where it works best, as it has a lot of built-in tools such as form integration, pre-validation, and so on; all of which are extremely useful for web applications. In addition to this, if you simply require basic queries, then Django would work out quite well since it is also much easier to learn.

However, if your web applications or frameworks require a little more complex queries, then SQLAlchemy is the one to go with. In addition to this, since it interacts directly with the database, you can simply run the queries against the database without actually using the ORM. Plus, SQLAlchemy is much more powerful than Django, albeit with a little higher learning curve.

Conclusion:

Both Django and SQLAlchemy are immensely popular object-relational mapping tools, having large communities to back them up and are used in a wide array of applications across the globe. Which one is more suited for you? That mainly depends on what your requirement needs are and where exactly do you want to use them. All in all, both are excellent choices for having as your ORM system.

About the author

Zeeman Memon

Zeeman Memon

Hi there! I'm a Software Engineer by degree, Blogger by skills who loves to write about tech, develop websites & do SEO. You can reach out to me on LinkedIn.