Enter the world of databases that think in connections, relationships, and networks - but beware of the common trap that catches most developers!
Remember those graph algorithms from computer science class? Shortest path, network traversal, connected components? Graph bring those to life!
Popular Examples: Neo4j, Amazon Neptune, ArangoDB
What they excel at:
The BIG Warning: 🚨 Just because you CAN model something as a graph doesn't mean you SHOULD!
Common mistake:
// DON'T do this just because you can!
User → OWNS → Car
User → LIVES_IN → City
User → WORKS_AT → Company
If you're just storing basic relationships without needing complex graph algorithms, use a regular database!
Use graph databases when you need:
Real example: LinkedIn uses graph databases to power "People You May Know" by analyzing complex relationship patterns across millions of users.
Key Insight: "Choose graph databases for their algorithms, not for their data modeling capabilities."
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