Webinars

Building Postgres High Availability That Holds Up Under Pressure

We dig into the scenarios teams most often overlook: replication lag during a failover, split-brain risks, fencing a demoted primary, and why automated failover can make an outage worse if not done carefully.

Multimodel Data Platforms in the Agentic Era

Join Lizzy Nguyen (EDB) and featured speaker Indranil Bandyopadhyay (Forrester), to dissect the multimodel data-platform market: where it's heading, what a converged approach unlocks, what enterprise buyers need to watch out for, and how to approach adoption.

From Live Transactions to In-Database Analytics and Machine Learning

Skip the CDC and ETL step between a transaction and your analysis.

Getting a live transaction in front of an analytical query or a machine learning workload usually means extra steps: a separate CDC tool captures the change, a custom ETL job transforms and loads it, and by the time the data lands in the warehouse, the moment to act on it has often passed.

Stop Managing Silos: A Modern Analytics Architecture Built on Postgres

We address the real trade-offs between converged and specialist systems, and what you need in place to make it perform.

Stateful on Kubernetes: Running Postgres the Right Way

We dig into the failure scenarios teams overlook, the trade-offs between self-managed and operator-managed approaches, and what it takes to build a Kubernetes-native Postgres setup you can actually trust in production.

The New Analytics Stack Is Converging. Who Will Own It?

Why Consolidating Your Analytics is Really a Question of Control? The analytics stack is converging, and the payoff is real: less duplicated data, fewer pipelines to maintain, faster time to insight. But convergence comes with a question: who’s in control?Many paths to a unified stack solve the pipeline problem, but force you to rely on vendor-controlled formats, engines, deployment, and cost, leaving your data strategy at their mercy. This session looks at convergence through the lens of ownership: what it takes to consolidate without giving up control — so you can own the full data lifecycle, from core operational data to long-term historical records to the agents that access them.