A Skeptics Guide to Graph Databases
summary
Argues graph databases excel when connections matter more than entities, showing a real Medicare dataset that surfaces a billion-dollar Medicare scam where a doctor billed $20–30M in a year, and a family‑tree project that drops load times from timeouts to sub-second family tree loads. Uses DataStax Enterprise Graph on Cassandra and Gremlin queries, warns about branching factors, algorithmic costs (PageRank O(n+m)), immature tooling, schema drift and costly queries that can halt production, and recommends small pilots not full rewrites.
AI-written summary · about
chapters (17)
- 0:00Intro
- 2:58What is a graph database?
- 3:53Where do graph databases fit?
- 8:25Graph is a hot trend
- 12:34Graph Use Cases
- 23:17Employee Hierarchy
- 24:51River Crossing Problem
- 25:22Constraint Problems
- 32:33Graph Computing Engine
- 35:29Labeled Property Graph
- 38:27Understand what you're looking for
- 39:27Understand what your tool is doing
- 40:21Understand your Algorithm
- 42:01Understand your Data
- 45:40Choose the Right Tool
- 49:27Yellow Light
- 55:46Questions?
related talks
55mA Practical Guide to Graph Databases
49mModern Graph Databases
01h 00mWho’s Afraid of Graphs?
19mUnraveling the Web of Relationships: Understanding Graph Data
26mGraph Databases will change your (freakin') life
56mWhat are Graph Databases and Why should I care?- 19mUnraveling the Web of Relationships: Understanding Graph Data
- 19mUnraveling the Web of Relationships: Understanding Graph Data