Question 1

What's the difference between a graph database and a relational database?

Accepted Answer

A relational database stores data in tables and typically joins tables to connect related records. A graph database stores data as nodes (things) and edges (relationships), making it faster and simpler to query many-to-many relationships and multi-hop connections (e.g., "friends of friends" or "paths" between entities). Relational databases can model relationships too, but complex joins can become harder to write and slower at scale for highly connected data.

Question 2

When should I use a graph database?

Accepted Answer

Use a graph database when relationships are central to your application and you need to traverse connections quickly. Common cases include social networks, recommendation engines, fraud rings and identity resolution, network/IT topology, knowledge graphs, and supply-chain dependency mapping. If your queries are mostly simple lookups, aggregations, or reporting on structured records, a relational or key-value database may be a better fit.

Question 3

How much does a graph database cost?

Accepted Answer

Cost depends on whether you use a managed cloud service or self-host. Managed services typically charge for compute (instance size/number of nodes), storage, I/O, backups, and data transfer. Costs rise with larger graphs, higher query throughput, and high availability (multi-zone/replicas). Self-hosting can reduce service fees but adds operational costs (engineering time, scaling, patching, monitoring). Always estimate based on expected graph size, read/write rates, and required uptime.

Graph Database

Definition

Real-World Example

Cloud Provider Equivalencies

Compare Across Cloud Providers

Explore More Cloud Computing Terms