High-Throughput Graph Abstraction at Netflix: Part I

Netflix developed a high-throughput graph abstraction designed to handle OLTP use cases requiring millions of operations per second on large graph datasets.

• •Property graph model with strongly typed nodes and edges for data consistency and efficient filtering
• •Architecture built on existing Netflix abstractions (KV, TimeSeries, EVCache) for persistence and caching
• •Graph schemas define node and edge types, properties, and relationships with direction specifications
• •Handling close to 10 million operations per second across 650 TB of graph data with low latency
• •Query optimizations include data validation, query planning, edge deduplication, and traversal path elimination

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