Databases and data management
Database characteristics
This article was originally published at https://gist.github.com/joepie91/f9df0b96c600b4fb3946e68a3a3344af.
NOTE: This is simplified. However, it's a useful high-level model for determining what kind of database you need for your project.
Data models
- Documents: Single type of thing, no relations
- Relational: Multiple types of things, relations between different types of things
- Graph: Single or multiple types of things, relations between different things of the same type
Consistency models
- Strong consistency: There is a single canonical view of the database, and everything connecting to any node in the database cluster is guaranteed to see the same data at the same moment in time.
- Eventual consistency: There can be multiple different views of the database (eg. different nodes in the cluster may have a different idea of what the current state of the data is), but once you stop changing stuff, they will eventually converge into a single view.
- No consistency: There's no guarantee that all nodes in the cluster will ever converge to the same view, whatsoever.
Schemafulness
- Schemaful: You know the format (fields, types, etc.) of the data upfront. Fields may be optional, but every field you use is defined in the schema upfront.
- Schemaless: You have no idea what the format is going to be. This is rarely applicable, and only really applies when dealing with storing data from a source that doesn't produce data in a reliable format.