Slow SQL Queries Are Killing Your Recommendation Engine
Blog post from Neo4j
In relational databases, complex data models require multiple tables and intermediate JOINs, whereas graph databases can be easily visualized on a whiteboard, making it intuitive for both developers and business domain experts. Graph databases enable answers to questions about data connections, such as the strength of relationships and characteristics of those connections, which is crucial for building recommendation engines. Unlike SQL queries, graph database queries are straightforward to write and understand, with their own syntax like Cypher, allowing users to traverse data relationships efficiently. The equivalent Cypher query for a recommendation engine can encompass six JOINs across tables, reducing performance issues associated with relational databases, making graph databases the best choice for building scalable recommendation engines.
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