Own Your Data Lifecycle: The Converged Analytics Series
Analytics is converging — Postgres, open lakehouses, and specialized engines are merging into one governed platform. This six-part series traces the full arc: why convergence is happening now, how Postgres data becomes a live analytical estate on Apache Iceberg, and how ClickHouse and WarehousePG query it together with zero duplication. From there, live demos show the model in action — real-time personalization, log and observability consolidation, and governed AI agent access — proving that moving less data, not moving it faster, is what makes an analytics stack defensible, auditable, and yours to control.
Governing EDB Postgres® AI at Scale with Red Hat Ansible
Part 1 of this series closed the deployment gap: automated provisioning, sub-30-second failover, and validated HA/DR that took one customer from 10 shared Postgres clusters to more than 500 individually managed instances, with automated failover replacing all hands incident response.
Own What's Next: Modernize Your Data Foundation for the AI Era with EDB and SUSE
Every enterprise database strategy is under the same pressure at once: control costs, escape proprietary lock-in, meet sovereignty requirements, and get ready for AI. Modernizing legacy databases, Oracle first, is often the opening move, but migration itself isn't the destination.
9월 EDB Postgres AI Summit Seoul 2026에서 큰 호응을 얻었던 'EDB AI 플랫폼 아키텍처' 세션의 Continue 편입니다. AI Data Platform/AI Agent로서의 EDB 제품 라인업부터 pgvector·vectorplus, AIDB Extension 기반 In-DB AI 파이프라인까지, 오픈소스 기반 AI 데이터 플랫폼을 실전 데모로 확인하세요.
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.
Agentic Analytics: From Legacy Architecture to Agentic Action on EDB Postgres AI
In this session, EDB experts Jack Christie, Dunith Danushka, and Malik Bilal explore how Converged Analytics on EDB Postgres AI capability unlocks agentic analytics workflows — without abandoning your existing data investments.
Postgres as Your AI Data Platform: Architecture, Vectors, and What to Watch Out For
We cover the architecture decisions that matter most, from data sovereignty and latency trade-offs to the operational challenges of running AI workloads alongside transactional ones. Leave with a clear picture of where Postgres fits in the modern AI stack.
EDB Summer Academy is a free virtual series covering high availability, Kubernetes, AI infrastructure, and analytics at scale. Each session goes beyond the basics, with practical depth you can apply straight away.
As organizations shift to agentic AI, the divide between transactional and warehouse data must disappear. To power AI agents that reason in real-time, you need a data platform that is modern, observable, sovereign, with governance built in. Join our live session to learn how EDB Postgres AI eliminates silos and simplifies your architecture across hybrid estates.
기업들이 에이전틱 AI(Agentic AI) 시대로 전환함에 따라, 트랜잭션 데이터와 데이터 웨어하우스 간의 경계는 허물어져야 합니다. 실시간으로 상황을 판단하고 추론하는 AI 에이전트를 원활하게 구동하기 위해서는 현대적이고 가시성이 확보되며, 데이터 주권과 강력한 거버넌스가 내장된 데이터 플랫폼이 필수적입니다.
