How many values accessed?

• Single-value (result single row)
  • 0-1
• Multiple-values
  • 0-n

Crud-type?

• read-only SELECT ...
• append-only INSERT INTO ...
• edit UPDATE VALUES ...
• delete DELETE FROM ...

CRUD-types -> frequency of each type

• see https://gpdb.docs.pivotal.io/43180/admin_guide/ddl/ddl-storage.html

Analysis queries

• Redis vs materialized view vs columnar vs hadoop/etc
• Predictability (cubes, rollups, how detailed?)

OLTP / OLAP

Read-order/area

• sequential / random
• sparse / tight
• rows / disk-block ratio?
• predictability? (think document vs normalized)
• swapping rate

Query size

• Query span fits in memory?
• Query result fits in memory?

Isolation-requirement

• isolation levels
• optimistic / pessimistic locking!
• event time? start / end of transaction

Durability requirements?

Recency level?

• eventual consistency ok?

Main-memory heavy operations?

• sort
• aggregates (?)
• joins

How much data?

How many accessors? (appliocation replicas)

• hotspots? vs easy sharding?

CPU usage?  - where condition evaluation cost?

Latency requirements

"Programming with read-only db"

Immutability

• temporal data

Event-driven database

• see http://dchambers.github.io/articles/databases-are-dead/

Time-series data

Insert data clustering

• Think citybikes