Graph Database Evaluation for a Financial Services Firm

The Challenge A financial services firm built a mature graph data ecosystem, but the graph database they selected originally did not scale as multiple business-critical solutions relied on graph data. As application and business teams across multiple stakeholder groups expanded usage, data volumes and concurrent usage increased, exposing systemic limitations. Cluster instability disrupted downstream pipelines, introducing delays and uncertainty into time-sensitive analytical and operational processes; while limitations in reasoning and fine-grained access controls constrained the firm’s ability to govern data, enforce consistent business logic, and safely expand analytical use across teams. An inflexible upgrade path left the client locked into outdated versions with unresolved bugs and pending feature requests. To compensate for gaps in platform capability, teams relied on manual processes and operational workarounds, requiring excessive time, stalling key workstreams, delaying decision making, and ultimately impeding the firm’s ability to evolve its graph platform from a tactical solution into a trusted, enterprise-level foundation for analytics and insight.