Trusted by nearly half of Fortune 100 companies, Nasdaq Boardvantage powers secure, intelligent board operations. In this deep dive session, explore how Azure Database for PostgreSQL and MySQL, Microsoft Foundry, Azure Kubernetes Service (AKS), and API Management create a resilient architecture that safeguards confidential data while unlocking new agentic AI capabilities.

Learn how to build an advanced AI agent using Azure Database for PostgreSQL and the new Microsoft Agent Framework. This hands-on lab walks you through integrating Retrieval-Augmented Generation (RAG), semantic re-ranking, Semantic Operators, and GraphRAG (using Apache AGE) to enable intelligent legal question-answering using real case data. Gain practical AI implementation skills with your own PostgreSQL-backed applications.

Please RSVP and arrive at least 5 minutes before the start time, at which point remaining spaces are open to standby attendees.

AI agents are reshaping business operations across sectors. If you’re looking to bolster your business with agents, this session offers a strategic approach for building intelligent agents that truly understand your data. Learn how to uncover next-level AI reasoning for your agents using knowledge graphs, vector search and the latest AI integrations directly in PostgreSQL on Azure. Leave with a blueprint and best practices from Azure customers you can use to augment your own apps and copilots.

Azure HorizonDB is Azure’s new fully managed PostgreSQL database for mission-critical workloads. Join engineering and product leaders to explore the architecture that enables enhanced scalability without sacrificing performance, ultra-fast failovers, and read replicas for constant availability. Learn how HorizonDB combines open-source Postgres with state-of-the-art Azure infrastructure, cutting-edge database innovation and advanced AI features to power next-generation applications.

Learn how to build an advanced AI agent using Azure Database for PostgreSQL and the new Microsoft Agent Framework. This hands-on lab walks you through integrating Retrieval-Augmented Generation (RAG), semantic re-ranking, Semantic Operators, and GraphRAG (using Apache AGE) to enable intelligent legal question-answering using real case data. Gain practical AI implementation skills with your own PostgreSQL-backed applications.

Please RSVP and arrive at least 5 minutes before the start time, at which point remaining spaces are open to standby attendees.

You probably don’t need a collection of specialty databases. Just use Postgres instead! Written for application developers and database pros, Just Use Postgres! shows you how to get the most out of the powerful Postgres database. In Just Use Postgres! you’ll learn how to: Use Postgres as an RDBMS for transactional workloads Develop generative AI, geospatial, and time-series applications Take advantage of modern SQL including window functions and CTEs Perform full-text search and process JSON documents Use Postgres as a message queue Optimize performance with various index types including B-trees, GIN, GiST, HNSW, and more Over the decades, PostgreSQL, aka Postgres, has grown into the most powerful general-purpose database and has become the de facto standard for developers worldwide. Just Use Postgres! takes a modern look at Postgres, exploring the database’s most up-to-date features for AI, time-series, full-text search, geospatial, and other application workloads. About the Technology You know that PostgreSQL is a fast, reliable, SQL compliant RDBMS. You may not know that it’s also great for geospatial systems, time series, full-text search, JSON documents, AI vector embeddings, and many other specialty database functions. For almost any data task you can imagine, you can use Postgres. About the Book Just Use Postgres! covers recipes for using Postgres in dozens of applications normally reserved for single-purpose databases. Written for busy application developers, each chapter explores a different use case illuminating the breadth and depth of Postgres’s capabilities. Along the way, you’ll also meet an incredible ecosystem of Postgres extensions like pgvector, PostGIS, pgmq, and TimescaleDB. You’ll be amazed at everything you can accomplish with Postgres! What's Inside Generative AI, geospatial, and time-series applications Modern SQL including window functions and CTEs Full-text search and JSON B-trees, GIN, GiST, HNSW, and more About the Reader For application developers, software engineers, and architects who know the basics of SQL. About the Author Denis Magda is a recognized Postgres expert and software engineer who worked on Java at Sun Microsystems and Oracle before focusing on databases and large-scale distributed systems. Quotes I was pleasantly surprised to learn many new things from this book. - From the Afterword by Vlad Mihalcea An excellent guide covering everything from basics to cutting-edge features. - Dave Cramer, PostgreSQL JDBC Maintainer Pleasant, easy to read with tonnes of great code. - Mike McQuillan, McQTech Ltd Well-organized and easy to search. - Edward Pollack, Microsoft Data Platform MVP The missing guide to understanding and using Postgres. - Mehboob Alam, POSTGRESNX, Inc.

With its unrivaled extensibility, PostgreSQL is a top choice for accelerating AI innovation. Now Azure is allowing developers to move even faster with Azure HorizonDB. Discover why Azure HorizonDB, which is AI-enabled out of the box, is the ideal launchpad for your apps and agents. We’ll demo the latest features, like AI Model Management and DiskANN Advanced Filtering, that make Postgres easy to provision and AI-aware on Azure.  See how you can build solutions faster with PostgreSQL.​

Discover how you can make the most of your IT estate migrations and modernizations with the newest AI capabilities. This session guides IT teams through assessing current environments, setting goals, and creating a business case with Azure Migrate for all of your workload types like Windows Server, SQL Server, .NET, Linux, PostgreSQL, Java, and more. We’ll explore tools to inventory workloads, map dependencies, and create actionable migration roadmaps.

In today’s AI-driven economy, data isn’t just an asset, it’s your differentiator. Join us for major announcements across Microsoft Fabric, Power BI, Azure SQL, and Azure PostgreSQL, and see how these innovations come together to deliver a unified, intelligent data foundation for AI. Experience customer success stories, live demos, and an inside look at the roadmap shaping the future of analytics, transactional workloads, and real-time insights all in one integrated experience.

Transform your data replication strategy into a competitive advantage with Oracle GoldenGate 23ai. This comprehensive guide delivers the practical knowledge DBAs and architects need to implement, optimize , and scale Oracle GoldenGate 23ai in production environments. Written by Oracle ACE Director Bobby Curtis, it blends deep technical expertise with real-world business insights from hundreds of implementations across manufacturing, financial services, and technology sectors. Beyond traditional replication, this book explores the groundbreaking capabilities that make GoldenGate 23ai essential for modern AI initiatives. Learn how to implement real-time vector replication for RAG systems, integrate with cloud platforms like GCP and Snowflake, and automate deployments using REST APIs and Python. Each chapter offers proven strategies to deliver measurable ROI while reducing operational risk. Whether you're upgrading from Classic GoldenGate , deploying your first cloud data pipeline, or building AI-ready data architectures, this book provides the strategic guidance and technical depth to succeed. With Bobby's signature direct approach, you'll avoid common pitfalls and implement best practices that scale with your business. What You Will Learn Master the microservices architecture and new capabilities of Oracle GoldenGate 23ai Implement secure, high-performance data replication across Oracle, PostgreSQL, and cloud databases Configure vector replication for AI and machine learning workloads, including RAG systems Design and build multi-master replication models with automatic conflict resolution Automate deployments and management using RESTful APIs and Python Optimize performance for sub-second replication lag in production environments Secure your replication environment with enterprise-grade features and compliance Upgrade from Classic to Microservices architecture with zero downtime Integrate with cloud platforms including OCI, GCP, AWS, and Azure Implement real-time data pipelines to BigQuery , Snowflake, and other cloud targets Navigate Oracle licensing models and optimize costs Who This Book Is For Database administrators, architects, and IT leaders working with Oracle GoldenGate —whether deploying for the first time, migrating from Classic architecture, or enabling AI-driven replication—will find actionable guidance on implementation, performance tuning, automation, and cloud integration. Covers unidirectional and multi-master replication and is packed with real-world use cases.

Kafka and Flink tend to get lumped in as "data services", in the sense that they process data, but in comparison to traditional databases they differ quite dramatically in functionality and utility. In this talk, we'll run through the lifetime of a write in Postgres to establish a baseline, understanding all the different services that data hits on its way down to the disk. Then we'll walk through writing data to a Kafka topic, and what 'writing' (or really, streaming) data to a Flink workflow looks like from a similar systems perspective. Along the way, we'll understand the key differences between the services and why some are more suited to long-term data storage than others.

Postgres and the Artificial Intelligence Landscape, artificial intelligence use has exploded, with much anticipation about its future. This talk explores many of the advances that has fueled this explosion, including multi-dimensional vectors, text embeddings, semantic/vector search, transformers, generative AI, and Retrieval-Augmented Generation (RAG). The talk includes semantic/vector search and RAG examples. It covers how the valuable data stored in databases can be used to enhance AI usage.

This talk is all about the surprising complexity of Postgres database migrations. It covers what factors makes a migration safe or unsafe, common pitfalls and introduces a tool to help mitigate them.

Come to this session to learn about Snowflake solutions for handling your transactional data. Hybrid Tables are tightly integrated into Snowflake providing a unified experience for transactional and analytical workloads, meaning no need for ETL. Postgres is an open source RDBMS loved by developers with very low latency reads and writes, and following the acquisition of Crunchy Data it will be coming to your Snowflake accounts. We'll describe the architectural differences between Postgres and Hybrid tables and help you navigate when to use which.

This book is your one-stop resource on PostgreSQL system architecture, installation, management, maintenance, and migration. It will help you address the critical needs driving successful database management today: reliability and availability, performance and scalability, security and compliance, cost-effectiveness and flexibility, disaster recovery, and real-time analytics—all in one volume. Each topic in the book is thoroughly explained by industry experts and includes step-by-step instructions for configuring the features, a discussion of common issues and their solutions, and an exploration of real-world scenarios and case studies that illustrate how concepts work in practice. You won't find the book's comprehensive coverage of advanced topics, including migration from Oracle to PostgreSQL, heterogeneous replication, and backup & recovery, in one place—online or anywhere else. What You Will Learn Install PostgreSQL using source code and yum installation Back up and recover Migrate from Oracle database to PostgreSQL using ora2pg utility Replicate from PostgreSQL to Oracle database and vice versa using Oracle GoldenGate Monitor using Grafana, PGAdmin, and command line tools Maintain with VACUUM, REINDEX, etc. Who This Book Is For Intermediate and advanced PostgreSQL users, including PostgreSQL administrators, architects, developers, analysts, disaster recovery system engineers, high availability engineers, and migration engineers

Large‑language‑model agents are only as useful as the context and tools they can reach.

Anthropic’s Model Context Protocol (MCP) proposes a universal, bidirectional interface that turns every external system—SQL databases, Slack, Git, web browsers, even your local file‑system—into first‑class “context providers.”

In just 30 minutes we’ll step from high‑level buzzwords to hands‑on engineering details:

• How MCP’s JSON‑RPC message format, streaming channels, and version‑negotiation work under the hood.
• Why per‑tool sandboxing via isolated client processes hardens security (and what happens when an LLM tries rm ‑rf /).
• Techniques for hierarchical context retrieval that stretch a model’s effective window beyond token limits.
• Real‑world patterns for accessing multiple tools—Postgres, Slack, GitHub—and plugging MCP into GenAI applications.

Expect code snippets and lessons from early adoption.

You’ll leave ready to wire your own services into any MCP‑aware model and level‑up your GenAI applications—without the N×M integration nightmare.

Send us a text This week on Making Data Simple, join Ajay Kulkarni, CEO and co-founder of TigerData, as we dive into the rapidly evolving world of data. Ajay shares his front-row perspective on the challenges and opportunities of building and scaling time-series databases in an era of AI-driven automation. From the mechanics of managing massive data streams to the bold bets shaping the future of IoT, this conversation goes deep into what’s breaking, what’s working, and what’s next. Whether you’re a data engineer, tech leader, or simply fascinated by the speed of AI innovation, this episode is packed with insights you won’t want to miss. 01:15 Meet AJ Kulkarni04:29 TigerData07:16 Timeseries 09:25 Use Cases 11:03 Why Progress? 11:58 Why TigerData16:05 AI is Everything21:06 The Fastest Postgres 25:45 Advanced Features28:53 Future of IOT36:48 The Future of TigerData38:03 San Francisco38:26 A Big Bet41:06 Good BooksLinkedIn: https://www.linkedin.com/in/ajaykulkarni/ Website:  https://tigerdata.com Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

At first, streaming Postgres changes into Iceberg feels like a no-brainer. You spin up Debezium or Kafka Connect, point it at Iceberg, and it all looks boringly straightforward. The surprise comes once the pipeline hits production. Replication slots vanish and start filling up WAL space, LSNs don't line up and cause duplicates or gaps, and Iceberg sinks fail in ways that push back all the way to your primary database. Then you throw in schema changes, backfills, and compaction, and suddenly the \"boring\" pipeline becomes a source of late-night firefights. In this talk, I'll share real stories from running Postgres to Iceberg CDC pipelines in production. We'll look at the unexpected problems that show up, why they happen, and the strategies that actually helped keep things stable. If you've ever thought of Postgres -> Iceberg as just plumbing, this session will show you why it's not so boring after all.

Software Architects choose tools and patterns with an eye toward cost, time, shelf-life, and standard features. Data API builder is not source generation — it's Microsoft's free Data API engine that exposes secure REST & GraphQL endpoints over SQL Server, Postgres, MySQL, and Azure Cosmos DB, whether in Azure, on-premises, or even in AWS or GCP. In this session, we'll discuss security & architecture options, and when to use GraphQL versus REST endpoints.

Discover how Nationale-Nederlanden revolutionized its database infrastructure in this compelling case study. Join Matheus as he unveils the strategic journey from legacy Oracle and SQL Server on-premises systems to Amazon Aurora PostgreSQL Serverless v2. Get practical insights into architectural decisions, migration strategies, and key lessons learned from one of Europe's largest financial institutions.