How We Store and Analyze a Large Social Graph
summary
Describes a system for storing and analyzing a very large social graph (over 100 million nodes and over 1 billion edges). Covers use cases from traversing a node's immediate neighbors to finding subgraphs that meet specific conditions, and explains handling continuous data ingestion in parallel with ongoing analysis.
AI-written summary · about
chapters (6)
- 0:00Graph databases intro
- 7:20Neo4j for graph analytics
- 22:03Dex (TigerGraph) for graphs
- 27:24Benchmarking single-machine
- 35:23Recommendations and conclusions
- 37:39Q&A on trade-offs
related talks
30mLarge Scale Graph Solutions: Use-cases and Lessons Learnt
48mAnalytics on Large Graphs in S3: Tools, Approaches and Formats for OLTP and OLAP
50mBig Data on Smallish Machines
49mModern Graph Databases
01h 00mGraph Mastery to AI
46mGraph Databases: Talking about your Data Relationships with Python
25mBuilding the World’s Largest Identity Graph without a Graph DB
27mGraphOne: A Data Store for Real-time Analytics on Evolving Graphs