NoSQL Data Modeler

Overview

Design data models for NoSQL databases including MongoDB (document), DynamoDB (key-value/wide-column), Redis (key-value), and Cassandra (wide-column). Unlike relational modeling where normalization drives design, NoSQL modeling starts from access patterns and query requirements, then shapes the data to serve those patterns efficiently.

Prerequisites

• mongosh, aws dynamodb CLI, redis-cli, or cqlsh installed depending on target database
• Documented list of application access patterns (read/write queries the application performs)
• Expected data volumes (document count, average document size, growth rate)
• Read/write ratio and latency requirements for each access pattern
• Understanding of consistency requirements (strong vs. eventual consistency)

Instructions

1. Catalog all application access patterns as a table with columns: pattern name, query description, frequency (queries/sec), latency requirement, and data fields accessed. This drives every modeling decision.

2. For MongoDB document modeling, apply the embedding vs. referencing decision framework:

   • Embed when: data is always accessed together, child data has no independent lifecycle, cardinality is bounded (1:few), and updates are infrequent.