u/RevolutionaryAd8906 , I appreciate your good intentions in creating a beginner-friendly tutorial like this. JSON is a core technology that anyone working with modern APIs should understand, and it's important to make learning accessible for beginners. That said, your mindset of setting up JSON to be thought of as a "database" is perhaps sub-optimal ... while it's useful to teach data persistence early on, positioning JSON as a database can set beginners up for struggles down the line. I think you know this, and I see where you're going with it, but fundamentally it sets up a paradigm in the heads of new programmers that is misaligned with best practices. JSON files are easy to use and understand, making them great for small projects or single-user applications. Maybe a to-do list or managing simple configuration settings, storing user preferences, tracking small collections (e.g., book or movie lists). JSON works well if the scale is very limited. The progression from using JSON for data storage to interacting with APIs is logical and effective. However the limitations of JSON are very quickly apparent: Scalability: JSON is not designed for large datasets (like managing a hotel............. maybe suggest a different example in your HOW TO?) Performance degrades significantly with thousands of records, as the entire file must be read and written each time. RAM also becomes a limiting factor. Beyond a few thousand records, load and save times will noticeably degrade, especially with detailed records. Concurrency: JSON does not handle concurrent access. When multiple users or processes interact with the data, conflicts and errors are likely. Traditional databases manage this with record locking, transactions, and ACID compliance. Data Integrity and Security: JSON lacks built-in features for enforcing data types, constraints, or relationships. Storing sensitive information in plain-text JSON without encryption is risky (like the hotel guests credit card numbers and addresses...??) Databases like SQLite or even NoSQL options like MongoDB help mitigate these issues. Integrating databases from the beginning with new programming students can be valuable and I would argue worth doing. It seems to me you're kicking a can down the line and instilling a bad notion in their heads that they can use JSON as a flat file database. SQLite, for instance, requires minimal setup and offers skills that are more transferable to complex projects. It introduces concepts like relationships, querying, and data normalization, which can save a lot of headaches later on. I wonder if there's a middle ground where you introduce data persistence with JSON, and then transition to something like SQLite or an ORM in short order? This would help beginners avoid the pitfalls of using JSON beyond its intended use while still learning important concepts in a manageable way. Anyway ... not trying to criticize too harshly, but I think this is a misguided way to teach what JSON is all about. More on reddit.com

Importantly: if the majority of ... using JSON, you might want to at least consider if a relational database is the right choice. That said, few applications are perfectly relational or document-oriented. Most applications have some mix of both. Here are some examples where I personally ... More on stackoverflow.com

Yes, but you would eventually end up reinventing something that looks like Mongodb, which does store its data in Json format, but also has a powerful engine and api, providing things like fast retrieval, search queries, clustering, etc. Why not just use something that's free, and that other people have already done the hard work for? More on reddit.com

I've written repository implementations that use JSON file as a datastore. But only in tests and local dev, never in production where a database is used as the datastore. A few reasons why JSON files aren't a good fit: JSON has poor type support (as does JS as a language) JSON is bloated when compared to DB implementations that use some sort of binary format: high memory usage when in-memory, higher disk usage when on-disk You need to write operations like filter, fetch, merge etc. your self that the database implementation drivers normally offer and hide from user (obviously this could be written as library code) ACID in databases are offered by the engine which you need to implement yourself. You mentioned data loss as one DB engines allow scaling vertically or horizontally if needed Database engines offer optimisations and indexing by way smarter people than either of us. Also the data can easily be crypted and backed up if desired So unless the projects have very few, non-concurrent users and you don't mind paying big bucks for a server, I'd suggest moving along with a database. Be it document store, key-value store or relational database More on reddit.com