NoSQL Patterns

What You'll Cover Today

Day 4 of Data Modeling in 5 Days pushes into advanced territory. You have enough foundation now to tackle real-world complexity. Today's exercise is more open-ended than earlier days — that's intentional.

document model

Understanding document model is the core goal of Day 4. The concept is straightforward once you see it in practice — most confusion comes from skipping the mental model and jumping straight to implementation. Start with the model, then write the code.

# document model — Working Example
# Study this pattern carefully before writing your own version

class documentmodelExample:
    """
    Demonstrates core document model concepts.
    Replace placeholder values with your real implementation.
    """
    
    def __init__(self, config: dict):
        self.config = config
        self._validate()
    
    def _validate(self):
        required = ['name', 'type']
        for field in required:
            if field not in self.config:
                raise ValueError(f"Missing required field: {field}")
    
    def process(self) -> dict:
        # Core logic goes here
        result = {
            'status': 'success',
            'topic': 'document model',
            'data': self.config
        }
        return result


# Usage
example = documentmodelExample({
    'name': 'my-implementation',
    'type': 'document model'
})
output = example.process()
print(output)

adjacency list

adjacency list is the practical application of document model in real projects. Once you understand the underlying model, adjacency list becomes the natural next step.

time-series

time-series rounds out today's lesson. It connects document model and adjacency list into a complete picture. You'll use all three concepts together in the exercise below.

Common Mistakes on Day 4

• Skipping the fundamentals — document model requires understanding the underlying model before you can apply it correctly. Read the section twice if needed.
• Ignoring error messages — error messages for adjacency list are usually precise. Read them carefully before searching online.
• Hard-coding values — anything that might change between environments belongs in configuration, not in your source code.
• Not testing edge cases — the happy path is not enough. What happens with empty input? With unexpected types? With network failures?