juhapekkaeloranta / data-access-patterns

Ideas/notes for a masters thesis

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data-access-patterns

  • 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

  • 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

  • Time-series data

  • Insert data clustering

    • Think citybikes

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Ideas/notes for a masters thesis