Data Warehouses

Separate database from OLTP systems - meant for analytics
ETL pipeline from OLTP systems to data warehouse

Implementation

There’s a middle fact table that links to other tables. The fact table represents each transaction

Columnar Storage

OLAP queries are based on only a few columns at a time and are frequently range-based
For OLAP, we use columnar storage instead of row-oriented storage that OLTP uses. An entry becomes a column instead of a row
- Thus the database because wide and short instead of tall and skinny

Column-Compression

Column layouts are good for column compression because we will have fewer distinct values in columns
We will have slower writes to the data warehouse but faster range-based and WHERE queries

Materialized View

since we don’t care as much about write speed and we do care about key analytics, we can also maintain things like averages that update with each write