Graph Database vs. Relational Database

Options you can choose from:

Graph Database

Stores data as nodes (things) and edges (connections between things). Ideal for data with many complex relationships, such as social networks, recommendation engines, or mapping how different items are connected.

Relational Database

Stores data in tables with rows and columns, like a spreadsheet. Well suited for applications where data has a clear, predictable structure, such as managing users, orders, or products.

Decision questions

Answer honestly according to the current needs of the project and data structure.

1. What type of data does your system process?

Structured records organized in tables — such as users, orders, or products A mix — mostly structured records, but with some complex relationships Highly connected data where the relationships between items are just as important as the items themselves

2. How often do you need to query data that is connected to other data?

Rarely — queries are simple, linking at most one or two tables Sometimes — some queries link several tables, but it is manageable Often — the data has many connections and I frequently need to follow chains of relationships

3. How much data do you have, and how fast is it growing?

Moderate amount of data — a standard database server can handle it Large amount of data with many connections between records Very large amounts of highly connected data (e.g., social networks, recommendation systems)

4. What is your team's experience with databases?

The team mainly has experience with traditional databases (e.g., PostgreSQL, MySQL) The team has experience with both types of databases The team has experience with graph databases (e.g., Neo4j, ArangoDB)

5. What kind of operations does your system mainly perform?

Creating, updating, and reading records reliably (e.g., placing orders, managing accounts) A mix of record management and querying connected data Finding connections, recommendations, shortest paths, or analysing networks of related items

6. How often does your data structure change or evolve?

Rarely — the data structure is fixed and well-defined from the start Sometimes — the structure is mostly stable but occasionally needs changes Often — new types of connections and data appear frequently and are hard to predict in advance

Result

Based on your answers, see the recommended solution below. 👇

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