Multigraph Topology for Scalable, Isolated Graph Workloads

FalcorDB's team conducted an assessment to evaluate the scalability of a multi-tenant graph database in handling access-permission workloads and its performance when transitioning from a single server to a clustered deployment. The study focused on a real-world query pattern—checking user permissions for files—and tested throughput across different hardware configurations, observing near-linear increases in query-per-second rates with each 32-core increment, thanks to minimal coordination overhead across shards. The database supports full graph isolation during queries, allowing each query to target a single graph key, which minimizes data leakage risks and maintains write integrity at the master level. FalcorDB's multigraph functionality, available in both open-source and managed versions, enables scalable read operations by adding replicas, though it does not support cross-graph queries within a single execution. Memory usage and snapshot time rise with more graphs, but query latency remains constant as each query is limited to a single graph. The platform is designed for technical teams managing complex, real-time data, enhancing accuracy in generative AI applications while reducing hallucinations in outputs.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.