Case Study: Innoplexus achieves 4–5x faster real-time KOL discovery and a simplified single-stack architecture with ArangoDB

ArangoDB one Database to Rule them all for Innoplexus’ KOL Discovery and Management Platform

Innoplexus, a provider of AI-driven Data as a Service and Continuous Analytics for industries like pharma and life sciences, needed a fast, distributed datastore for its kPlexus™ KOL discovery and management platform that analyzes roughly 10 million profiles in real time. The platform originally depended on multiple systems (MongoDB, Elasticsearch, Neo4j, Redis), creating high maintenance overhead, data redundancy and performance constraints.

Innoplexus adopted ArangoDB’s multi-model database (using the MMFiles storage engine) to store graphs and documents together, replace Neo4j and Elasticsearch functionality, and leverage AQL joins and full‑text search. With ArangoDB they eliminated duplicated copies, achieved 4–5x faster performance on complex graph queries versus Neo4j, support ~75 GB of data with tens of millions of nodes and ~0.5 billion edges, and reduced developer effort and infrastructure costs while delivering faster real‑time responses.

Innoplexus

Akshesh Doshi

Software & Data Engineer