Most attempts to unify analytics still move data to get the job done: faster pipelines, tighter syncs, more automated ETL. That's real progress, but it's still movement — and every copy created has a cost, whether it shows up as stale data, bloated bills, or lost control over where data lives and who can touch it.
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.
최근 기업용 AI 도입이 가속화되면서, 데이터를 어떻게 효율적으로 관리하고 AI 모델과 결합할 것인지가 비즈니스의 핵심 과제가 되었습니다.
이에 EDB는 오픈소스 기반 Postgres의 강력한 성능을 AI 환경에 최적화하여 활용할 수 있는 3부작 웨비나 시리즈를 준비했습니다. 단순한 이론을 넘어 실무 데모와 하이브리드 관리 전략까지, EDB가 제시하는 AI 데이터 인프라의 미래를 직접 확인해 보시기 바랍니다.
WarehousePG—the sovereign data warehouse built on EDB Postgres® AI (EDB PG AI)—is designed to break this bottleneck. By leveraging Massively Parallel Processing (MPP) architecture, WarehousePG provides a stable, petabyte-scale analytical database that thrives under high concurrency.
PostgreSQL vs. MySQL: Choosing the Right Foundation
The webinar discussed the current state and future prospects of MySQL and Postgres databases, emphasizing the advantages of Postgres for modern data platform needs. MySQL, once a leading database for web applications, has seen a decline in investment and innovation, particularly after Oracle's acquisition, leading to reduced community contributions and fewer resources. In contrast, Postgres has grown significantly, supported by a vibrant open-source community and substantial investments from EDB.
EDB Postgres AI Factory: Learn How to Operate GenAI and Agentic Data Workloads
The demand for rapid innovation clashes with the need for data sovereignty, security, and efficiency. Stop struggling with complex, time-consuming integrations that sacrifice control and governance.
Build with EDB Postgres® AI: Part 5: Working with Time-Series Data in Postgres
Unlock advanced time-series analytics in PostgreSQL using the Bluefin extension. Learn how to analyze financial transactions, IoT data, and seasonal trends efficiently within Postgres—ideal for AI-driven forecasting, anomaly detection, and predictive analytics.
Build with EDB Postgres® AI: Part 4: Agentic Analytics with AI Agents
See how to develop AI agents for analytics. Learn how PostgreSQL can fuel data-driven conversation, enabling teams to interact with business data and automate decision-making opportunities.
