How Securin Runs 7-Hop Threat Intelligence Queries in Under 350ms with FalkorDB

Securin, a cybersecurity intelligence company, faced significant challenges with their previous graph database, which experienced high latency and frequent timeouts during deep multi-hop queries essential for their AI-powered threat intelligence platform. These limitations undermined user trust and performance, particularly as their queries often exceeded the 5-hop threshold where the previous system would fail. By migrating to FalkorDB, Securin achieved a drastic improvement with a success rate of 100% across 170 benchmark queries compared to the previous 76.47%, reduced average query latency from 1.43 seconds to 0.33 seconds, and decreased overall agent response time from approximately 15 seconds to under 3 seconds. FalkorDB's architecture, leveraging sparse matrix representation and in-memory execution, enabled efficient handling of complex queries without the latency overhead of network I/O, thus meeting Securin's stringent performance requirements and restoring user confidence in their AI capabilities.

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.