Saga: A Platform for Continuous Construction and Serving of Knowledge At Scale

TL;DR

Saga is a scalable platform that continuously constructs and serves a large knowledge graph, addressing industrial challenges in data freshness, accuracy, and availability for diverse knowledge-based applications.

Contribution

The paper presents Saga, a hybrid batch-incremental system for large-scale knowledge graph construction and serving, with insights from real-world industrial deployments.

Findings

Successfully integrated billions of facts into a knowledge graph.

Supported diverse production use cases with varying data requirements.

Provided lessons learned from extensive industrial applications.

Abstract

We introduce Saga, a next-generation knowledge construction and serving platform for powering knowledge-based applications at industrial scale. Saga follows a hybrid batch-incremental design to continuously integrate billions of facts about real-world entities and construct a central knowledge graph that supports multiple production use cases with diverse requirements around data freshness, accuracy, and availability. In this paper, we discuss the unique challenges associated with knowledge graph construction at industrial scale, and review the main components of Saga and how they address these challenges. Finally, we share lessons-learned from a wide array of production use cases powered by Saga.