Netflix Real-Time Distributed Graph: Query Engine Design

Understand the key design decisions behind Netflix's graph query serving layer — BFS traversal, async thread pools, volatility-aware caching, configurable filtering, and adaptive concurrency — and know when to apply these patterns in your own systems.

4 sections · 8 lessons

Course outline

Graph Traversal at Scale

  1. Why BFS beats DFS for distributed graphs
  2. From sequential calls to parallel batches

Async-First Concurrency

  1. Why thread-per-request doesn't scale
  2. 16-24 threads serving thousands of concurrent queries

Volatility-Aware Caching

  1. The problem with uniform TTLs
  2. Mapping TTL to data change rate

Configurable Filtering and Adaptive Concurrency

  1. Filtering hierarchy: global, per-hop, per-edge-type
  2. Asymmetric concurrency limiting

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