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A Quick and Comprehensive Guide On Which Database to Use in your next Fullstack Application

In the ever-evolving world of technology, we can safely say that there is this one constant (🥳), the backbone of most applications — whether they're your go-to weather app or the database managing global transactions — is the database management system (DBMS) they rely on. Building fullstack applications made me want to gather in one place my notes and takeaways from different databases, which hopefully will also help you see clearer, and make an informed decision on which database to use, and why.

So this is a short and sweet guide on the main three databases most used today: SQLite, PostgreSQL, and MongoDB. Each of these powerhouses offers unique features, advantages, and typical use cases. Let's dive in!

SQLite - The Lightweight Champion 🕊️

Imagine a tiny, yet mighty warrior—that's SQLite! It's the database equivalent of having a Swiss Army knife in your pocket. It is designed to be embedded within the application it powers: SQLite is a self-contained, disk-based database that doesn't fuss over needing a separate server process.


  • Lightweight and Portable: Effortless setup, ideal for constrained environments.
  • No Installation Needed: Seamless integration with applications, simplifying deployment.
  • Reliable and Accessible: A robust storage solution that's straightforward to manage.


  • Limited Scalability: Not the best fit for high-traffic scenarios or concurrent writes.
  • Fewer Features: Misses out on some advanced functionalities of more complex systems.

Famous Use Case:

Apple makes extensive use of SQLite across macOS and iOS, embedding it within various system functions and applications, showcasing its reliability and efficiency.

PostgreSQL: The Robust Workhorse 🏋️‍♂️

Here we are dealing with object-relational database system that's all about reliability, robust features, and performance. It's like having a reliable workhorse that can carry heavy loads without breaking a sweat. PostgreSQL shines then in enterprise applications, web services, data warehousing, or geospatial databases thanks to its scalability and advanced features.
A big plus for PostgreSQL is that it's open-source 😎


  • Highly Scalable: made to handle large datasets and numerous concurrent users.
  • Advanced Features: Rich in functionalities like complex queries and transactions.
  • Extensibility: Custom data types and functions for tailored solutions.


  • Complexity: Its sophistication can be a hurdle for smaller teams or projects.
  • Resource Intensive: Requires a significant investment in hardware and upkeep.

Famous Use Case:

:drum-roll: Instagram!

MongoDB: The Agile NoSQL 🐐

Finally, let's talk about MongoDB, the NoSQL database that's all about flexibility and speed. Picture a gymnast performing a flawless routine—graceful, flexible, and powerful. That's MongoDB, storing data in flexible, JSON-like documents which allows fields to vary and data structure to change over time. It's perfect for big data applications, content management systems, and mobile apps requiring real-time data.


  • High Performance: Designed for rapid data retrieval and large data volumes.
  • Scalability: Sharding capability for distributing data across servers.
  • Flexible Schema: Adapts to polymorphic data, perfect for changing data models.


  • Awkward Joins: Performing joins is less straightforward than in relational databases.
  • Memory Usage: Potentially high, which could be restrictive in certain environments.

Famous Use Case:

Meta utilizes MongoDB for its diverse set of applications.

Making the Choice

Choosing between SQLite, PostgreSQL, and MongoDB isn't about picking the best database overall — it's about finding the best fit for your project's needs. If simplicity and ease of use are paramount, SQLite might be your best choice. For projects requiring data integrity, complex queries, and scalability, PostgreSQL stands ready to support you in that. And for scenarios demanding flexibility, scalability, and high performance, especially with large volumes of unstructured data, MongoDB might be the way to go.

Thanks for reading, and happy coding 👋

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