Real-Time Analytics: Oldcastle Integrates Infor with Amazon Aurora and Amazon Quick Sight

Why It Matters

The move shows cloud ERP migrations can retain, and even enhance, real‑time reporting, giving enterprises faster decision‑making and higher productivity. It provides a repeatable blueprint for firms combining ERP data with AWS analytics and AI services.

Key Takeaways

• Oldcastle deployed 50+ real-time dashboards in eight months using Aurora and QuickSight.
• Stream Pipelines feed data directly to Aurora, eliminating batch reporting delays.
• RDS Proxy and NLB ensure high‑availability connections for over 100 concurrent users.
• QuickSight embedding via API Gateway provides seamless analytics inside Infor ERP.
• Architecture scales to millions of daily transactions with automatic Aurora read‑replica scaling.

Pulse Analysis

Enterprises shifting legacy ERP systems to the cloud often sacrifice the immediacy of operational reporting, relying on batch processes that delay critical insights. Infor’s traditional cloud ERP reporting tools provide only a limited set of static reports, leaving manufacturers, logistics providers, and finance teams without the granular, real‑time data needed to respond to market fluctuations. This gap has driven a wave of demand for streaming architectures that can ingest, transform, and visualize data as it changes, ensuring decision‑makers have up‑to‑the‑minute visibility across the organization.

Oldcastle’s solution stitches together several AWS services to meet that demand. Infor Data Fabric Stream Pipelines captures insert, update, and delete events from ERP tables and pushes them through a Network Load Balancer to an Amazon Aurora PostgreSQL cluster, where RDS Proxy pools connections for high‑throughput, fault‑tolerant access. QuickSight, connected via VPC and secured with Secrets Manager, renders interactive dashboards that are embedded directly into the Infor UI through API Gateway and Lambda‑generated signed URLs. The architecture delivers sub‑second query performance via SPICE caching, supports over 100 concurrent users, and automatically scales Aurora read replicas to handle millions of daily transactions.

The broader implication is a template for any large‑scale enterprise seeking to modernize ERP analytics without losing real‑time capability. By combining streaming data pipelines with cloud‑native databases and embedded BI, companies can unlock new AI and machine‑learning use cases—such as demand forecasting and intelligent search—while maintaining a seamless user experience. As more firms adopt similar patterns, the market will likely see a shift toward integrated, AI‑ready ERP ecosystems that turn operational data into a continuous competitive advantage.