Sovereign Data Strategies: Scaling Postgres for Large Scale Analytics

May 12 | 9 a.m. PT/12 p.m. ET

As data volumes continue to grow at around 40% annually, the cloud-first promise of effortless scale has hit a wall of unpredictable consumption costs and vendor lock-in. Many organizations now find themselves renting their insights through proprietary platforms, sacrificing data sovereignty and architectural flexibility in the process. To regain control, leaders are moving toward sovereign analytics; infrastructure that offers cloud-level performance without the cloud-provider tax.

Join us for a technical discussion grounded in business outcomes. We will explore WarehousePG, the parallel processing platform that transforms PostgreSQL into a petabyte-scale powerhouse with integrations across the data stack from transactional, to the lakehouse and AI workloads.

This session explores how Postgres parallel processing architecture achieves petabyte-scale analytics while bypassing the constraints of legacy appliances and costly cloud services. We will demonstrate how to deploy this high-performance framework across on-premises, cloud, and hybrid environments.

Key takeaways:

• Scalable Open Architecture: How Postgres parallel processing architecture enables petabyte-scale analytics without relying on proprietary hardware.
• Cloud vs. Sovereign Economics: A practical analysis of cost tradeoffs between native cloud services and sovereign alternatives, and framework for choosing the optimal environment (on-prem, cloud, or hybrid).
• Strategic Ownership & Modernization: Navigating vendor lock-in, data portability, and long-term sovereignty with strategies to upgrade your analytics infrastructure without a total refactor.
• AI-ready data foundation: How to query external data on cheaper object storage, simplify the data pipeline, and get AI to market faster.

Get the information required to navigate today’s shift to sovereign data and AI platforms, learn how to get the performance of a modern warehouse with the freedom and familiarity of Postgres.