Tenant Isolation Strategies in Shared Graph Infrastructure: Balancing Security, Performance, And Cost Efficiency

Abstract

Multi-tenant graph databases in enterprise systems present significant challenges in balancing strict tenant isolation with query performance and cost efficiency. Graph databases preserve relationship complexity that relational systems struggle to represent efficiently; consequently, multi-hop traversals in shared environments risk exposing cross-tenant data boundaries. This paper evaluates three tenant isolation strategies—Property-Based Isolation (PBI), Path-Based Isolation (PATH), and Graph Partition Isolation (GPI)—across security guarantees, query latency, storage overhead, and operational cost. Experimental evaluation using enterprise-scale workloads (up to 150 million nodes) with concurrent queries demonstrates that Graph Partition Isolation (GPI) reduces query response time by 40-60 percent and eliminates unauthorized cross-tenant access while maintaining manageable storage overhead and predictable operational costs. Real-time validation of tenant boundaries by automated verification based on graph structure has the benefit of ensuring security. These results demonstrate that carefully designed partitioning combined with traversal-level isolation mechanisms enable multi-tenant graph systems to achieve enterprise-grade security without sacrificing performance or cost efficiency, providing practical guidance for selecting appropriate isolation strategies based on workload characteristics, scale, and cost constraints.