SQL vs NoSQL

table.md

SQL	NoSQL
When your access patterns aren't defined	When your access pattern is defined.
When you want to perform flexible queries. If your access patterns arent define you won't know what queries to perform.	When your primary key is known.
When you want to perform relational queries.	When your data model fits (graphs)
When you want to enforce field constraints, this allows you to keep your data consistent.	High efficiency Scaling
When you want to use a documented access language (SQL) is generally universal across all the Relational Database Engines.	When you need high performance and low latency.
Data use Schemes	Schema-less
Relations!	No (very few) Relations
Data is distributed across multiple tables	Data is typically merged and nested in a few collections
Horizontal scaling is difficicult/impossible; vertical scaling is possible	Both horizontal and vertical scaling is possible
Limitations for lots of (thousand) read & write queries per second.	Great performance for mass (simple) read & write queries.
Structured data can be stored in tables	Using JSON data un-structured data can be stored.