Question 1

What's the difference between a document database and a relational database (SQL)?

Accepted Answer

A relational database stores data in tables with fixed columns and uses joins to connect related data. A document database stores each record as a document (often JSON-like) where fields can vary between documents, and related data is often embedded (nested) inside a single document. SQL databases are great for strong consistency and complex joins; document databases are great for flexible schemas and fast development when data shapes change often.

Question 2

When should I use a document database?

Accepted Answer

Use a document database when your data is naturally JSON-like, varies by record, or changes frequently (e.g., CMS articles with different metadata, user profiles with optional fields, product catalogs with different attributes per category). It’s also a good fit when you want to retrieve an entire object in one read (a single document) and avoid many joins. If you need heavy relational joins, strict normalization, or complex multi-row transactions across many entities, a relational database may be a better default.

Question 3

How much does a document database cost?

Accepted Answer

Cost depends on whether it’s serverless or provisioned, and on throughput, storage, and data transfer. Common pricing factors include: (1) read/write operations or provisioned capacity (e.g., RU/s in Cosmos DB, read/write capacity units in some services), (2) storage size (GB), (3) replication and multi-region deployments, (4) backups and retention, and (5) network egress. Serverless options can reduce cost for spiky workloads, while provisioned capacity can be cheaper for steady, predictable traffic.

Document Database

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