Exploring the often overlooked third dimension of database storage models, the blog post delves into the distinctions between row-based, column-based, and network-based (graph) databases, highlighting their unique advantages and use cases. Row-based databases like MySQL and PostgreSQL excel in transactional processing with quick record modifications, while column-based databases such as Cassandra and Amazon Redshift are ideal for analytical tasks requiring large-scale data aggregation. The network-based model, or graph databases like Neo4j, introduces a third dimension by focusing on the relationships between data points, with FalkorDB innovating by optimizing edge storage using adjacency matrices instead of lists. This approach is particularly suited for use cases needing efficient traversal of data relationships. The choice of database model should align with specific data needs, and hybrid approaches may enhance performance and functionality. The post is authored by Guy Korland, CEO of FalkorDB, who has a rich background in database engineering and leadership roles.