Embedded Analytics Modernization for a Payroll SaaS Platform

The situation

A multi-tenant enterprise payroll SaaS platform serving organizations across two countries was undergoing a major architectural transformation, migrating from a monolithic application to an event-sourced architecture with Azure Event Hubs as the event backbone. The legacy reporting system was a significant pain point: reports took up to 45 minutes or timed out entirely. Analytical and transactional workloads competed for the same resources, and reporting could not scale independently of core payroll operations.

The platform needed an embedded analytics layer that could serve payslip reports, payroll registers, and leave balance reports with sub-second latency. The data needed to be fresh within minutes, not hours. All data processing had to remain within the client’s cloud tenant for data sovereignty compliance. And the solution needed to support time travel for audit requirements, allowing any historical report to be reproduced at any point in time.

What we built

CorrDyn designed and validated a proof of concept for an embedded analytics architecture built on Estuary BYOC, DuckLake, and DuckDB.

Event stream ingestion. The platform’s event-sourced architecture publishes domain events to Azure Event Hubs using the Kafka API. Estuary BYOC (Bring Your Own Cloud), deployed entirely within the client’s Azure tenant, captures these event streams and lands them in structured storage. Running Estuary within the client’s infrastructure satisfies data sovereignty requirements without data leaving the tenant boundary.

Analytical storage layer. DuckLake provides the catalog and storage layer, with a PostgreSQL catalog backend for metadata and versioning. This enables time travel: the system can reproduce the state of any report at any historical point by querying against the catalog’s version history. Schema denormalization handles the complex JSON payloads from the event streams, transforming them into query-optimized structures.

Query engine. DuckDB serves as the analytical query engine, delivering sub-second latency for the three target report types. Multi-tenant isolation is enforced through physical partitioning by company code, ensuring that each tenant’s queries only scan their own data. The engine runs embedded within the application, eliminating the network round-trip overhead of a separate data warehouse service.

Cost analysis and architecture comparison. CorrDyn prepared a detailed comparison between the validated stack and Microsoft Fabric as the enterprise alternative. The analysis covered cost modeling, query performance, data freshness, data sovereignty compliance, vendor risk, and operational complexity. The open-source stack projected at roughly $71,000 per year, compared to approximately $300,000 for the Fabric alternative.

What changed

The proof of concept demonstrated that the payroll platform can serve embedded analytical reports with sub-second latency and near-real-time data freshness at a fraction of the cost of enterprise alternatives. Reports that previously took 45 minutes or timed out entirely now return in under a second. The architecture supports the platform’s event-sourced migration path, meets data sovereignty and audit compliance requirements, and provides a scalable foundation for expanding the embedded analytics surface as the product evolves.