Building Your First Knowledge Graph: A Practical Guide from Schema to Query

You've got a recommendation engine that's slow, a fraud detection system drowning in JOINs, or a content platform where "related items" queries take seconds instead of milliseconds. Relational databases excel at many things, but traversing complex relationships isn't one of them. Consider a simple question: "Show me products purchased by users who bought items similar to what this customer browsed last week." In SQL, you're looking at a multi-table join that grows exponentially with each hop through the relationship chain. Add another degree of separation—friends of friends, transactions linked through shared accounts, content connected by overlapping tags—and your query optimizer starts making choices you'd rather not debug at 2 AM. The fundamental issue isn't your indexing strategy or query tuning skills. It's architectural. Relational databases store relationships as foreign keys scattered across tables, requiring expensive join operations to reconstruct connections at query time. W