Yelp Graph-Relational Modeling with EdgeDB

πŸ“˜ Description

This project explores the use of EdgeDB to create a hybrid graph-relational schema for Yelp business and review data in Chicago. The module focuses on modeling complex relationships such as user-review-business interactions, and using EdgeQL to extract insights through recursive queries and filters.

Developed for the MSDS 420 course at Northwestern, the assignment applies modern database design concepts to a real-world dataset, showcasing how graph-relational databases bridge the gap between flexibility and structure.

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πŸ”§ Features

  • EdgeDB Modeling: Defines object types and links to model Yelp businesses, users, reviews, and locations.
  • Recursive Relationships: Tracks influence of reviews across users and locations using recursive EdgeQL.
  • Query Optimization: Uses filters, sorting, and set-based logic for efficient insight extraction.
  • Graph-Relational Design: Combines schema integrity with flexible query structures in EdgeDB.
  • Real-World Application: Demonstrates the strengths of graph-relational modeling for complex datasets.

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πŸ’‘ Key Insight

EdgeDB’s hybrid model enables a more natural expression of real-world relationships, reducing the complexity of JOINs and enabling elegant recursive queries β€” a perfect fit for applications like Yelp.

πŸ”— View the source code on GitHub