in data modeling discussions I often hear the phrase “non-relational data”. It’s usually someone making a case for why data should be in a NoSQL store or just denormalized in general. The argument is usually that the data itself is somehow inherently “non-relational” and so it should be put in a non-relational database.
calling data non-relational is like a short-hand for saying that some of the data doesn’t change and therefore is better served to be stored in a non-relational store. For instance, if you’re storing user analytics data and each user has many devices. There’s a one to many between a user and their devices, but if the devices list is append-only and you’ll never have to mutate any individual device, maybe there’s no need to have a normalized representation between users and devices that requires you to pay processing time for reads which require JOINs.
{
"_id": ObjectId("5f5a1f5e3dc1264c7ee03d5a"),
"username": "john_doe",
"email": "[email protected]",
"devices": [
{
"device_id": "123456789",
"device_name": "Smartphone",
"os": "iOS"
},
{
"device_id": "987654321",
"device_name": "Laptop",
"os": "Windows"
},
{
"device_id": "567890123",
"device_name": "Tablet",
"os": "Android"
}
]
}
Code language: JSON / JSON with Comments (json)still, I don’t think that makes the data non-relational – there’s a one to many relationship. It does mean that there’s a processing performance trade-off if it’s stored in a normalized form (which by the way you can also do in a non-relational database).
in reality, most complex data have relationships like these and every conversation about storage systems is fundamentally about how to most effectively store and fetch that data. Depending on the use cases and constraints, that data may be stored in a relational database or a non-relational database, but the data itself is not inherently “non-relational”.