Modernising Neo4j for a Global Recruiting SaaS Platform

Industry: SaaS & Digital Businesses / HR & Recruiting Tech

Region: EMEA

Company Size: Scale-up

Use Case: Graph database migration and modernisation on AWS

Products Used: Neo4j AuraDB, AWS Marketplace, AWS Secrets Manager, Amazon CloudWatch, AWS IAM

Company Overview
A leading recruiting SaaS provider relied on a self-managed Neo4j 4.2 deployment on AWS to power their core graph-based workflows. As data volumes and global traffic grew, the single-node setup became harder to scale, maintain, and secure. The company turned to VeUP to modernise its graph platform and migrate to Neo4j AuraDB, a fully managed graph database service available via AWS Marketplace.

Challenge
The platform was running on a single-node Neo4j instance tightly coupled to legacy drivers in Java, Python, and Node.js. Scaling ceilings, manual backup and recovery processes, and fragmented security controls increased operational risk as the business grew. There was no automated failover, no integrated secrets management, and accumulating technical debt around drivers and connection pooling made it difficult to evolve the stack safely.

Solution
VeUP delivered a zero-downtime migration from self-managed Neo4j 4.2 to Neo4j 5.1 on AuraDB, combining platform upgrade, driver modernisation, and security hardening. The team audited all microservices and upgraded them to the latest official Neo4j drivers across Java, Python, and Node.js, redesigning connection pooling to leverage AuraDB’s managed cluster context. AWS Secrets Manager was integrated to centralise credential rotation and access control, and a full rollback and restoration plan—covering snapshots, backups, and driver fallback—was implemented and tested to de-risk cutover. Engineering teams were trained on AuraDB’s console, monitoring, and operational playbooks so they could confidently run, observe, and scale the new environment.

Platform upgrade to Neo4j AuraDB: Migrated from a single-node Neo4j 4.2 instance to Neo4j 5.1 on AuraDB managed clusters, gaining high availability, automated failover, and SLA-backed reliability.
Driver and pooling modernisation: Audited all Java, Python, and Node.js services and upgraded them to current Neo4j drivers, redesigning connection pooling to reduce latency and improve stability.
Security and secrets management: Integrated AWS Secrets Manager for secure credential storage and rotation, aligning graph access with the organisation’s security and compliance requirements.
Rollback and operational readiness: Built and tested a rollback plan with snapshots, backups, and driver fallback paths, and trained engineering squads on monitoring, incident response, patching, and compliance workflows for AuraDB.

Results

99.9% uptime with automated failover, eliminating previous downtime incidents
75% reduction in database operational overhead and manual maintenance tasks
Modern, supportable driver stack ready for future feature adoption
Stronger security posture through centralised secrets and access control

Looking Ahead
With a managed Neo4j AuraDB foundation in place, the recruiting platform can now scale graph workloads without worrying about node limits, manual backups, or fragile failover. The modern driver stack and security model make it easier to roll out new graph features, expand globally, and respond to changing product requirements.

Thinking of Modernising Your Data Platform?
If you’re running a self-managed graph database or legacy data stack that’s becoming hard to scale and secure, VeUP’s engineering teams can help you modernise on AWS while keeping your applications online. From Neo4j to relational and streaming platforms, we design migrations that reduce operational burden and unlock headroom for your product to grow.

Achievements

Managed Neo4j Upgrade

Migrated from a self-managed Neo4j 4.2 instance to Neo4j AuraDB 5.1, gaining automated failover, cluster reliability, and SLA-backed uptime.

Modernised Driver Ecosystem

Upgraded Java, Python, and Node.js services to the latest Neo4j drivers, improving connection stability and reducing latency across all graph queries.

Secure Credential Management

Integrated AWS Secrets Manager to centralise credential rotation and strengthen access control across all microservices connecting to AuraDB.

Optimised Connection Pooling

Redesigned connection pooling logic to make full use of AuraDB’s managed cluster behaviour, improving throughput and reducing runtime errors.

Rollback and Recovery Readiness

Built and tested a full restoration playbook—including snapshots, backups, and driver fallback paths—to ensure safe, low-risk migration. Operational Uplift for Engineering Teams Delivered training, monitoring dashboards, and operational playbooks to give engineering teams ownership and confidence in the modernised platform.