Relational-Core Graph Analytics Querying graphs at SQL scale, and why the node/edge model is a performance tax, not a truer picture of connected data
Paper recorded by Signals 4 on 2026-09-01 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-01 on arXiv · recorded by Signals 4 on 2026-09-02
Category: cs.AI · 人工智能 · first seen 2026-09-02
Abstract
A durable assumption holds that graph analytics requires a purpose-built graph engine, and that relational systems are ill-suited to connected data. We argue the opposite for the workloads enterprises actually run. A columnar relational engine fronted by a graph query language matches or exceeds native graph engines on analytical graph queries, and - decisively - scales past the point where in-mem
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Cite this page: Relational-Core Graph Analytics Querying graphs at SQL scale, and why the node/edge model is a performance tax, not a truer picture of connected data: the #237 most recent of 300 cs.AI papers we have recorded (as of 2026-09-01). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/relational-core-graph-analytics-querying-graphs-at-sql-scale-and-why-the-node-ed.html
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