Ruiqi Jiang explains how the APEX Graph Visualization Plug-in brings Oracle Graph into Oracle APEX applications for interactive exploration of connected data. Developers can visualize vertices and edges, adjust graph layouts, filter data, customize styling, and connect graph interactions with APEX application processes.

In this episode of Digital Impact Radio Series 9, Franco Ucci speaks with Ruiqi Jiang about Oracle Graph and the APEX Graph Visualization Plug-in, which brings interactive property graph visualization into Oracle APEX applications. Ruiqi explains how Oracle Graph provides built-in capabilities in Oracle Database for representing and querying connected data using property graphs, while the plug-in provides a front-end visualization layer that developers can add as a region within an APEX application.

The conversation explores how developers can use the plug-in to render and interact with vertices and edges, change graph layouts, group or ungroup elements, filter connected data, and customize the appearance of graph visualizations. Ruiqi also discusses ways to provide richer application experiences through node tooltips, interactive page redirects, and AJAX processes.

The episode also looks at the broader developer experience around graph technology, including the GVT library, JavaScript, Visual Studio Code, Python, and Jupyter notebooks. For developers working with Oracle APEX and connected data, the discussion provides an introduction to combining Oracle Graph capabilities with interactive application experiences.

Oracle LiveStacks helps learners explore working, industry-relevant applications before diving into the technologies and architecture behind them. Kevin Lazarz and Matt Howalik explain how LiveStacks combines Oracle LiveLabs with Oracle AI Database 26ai capabilities to connect business outcomes with practical hands-on learning.

In this episode of Digital Impact Radio Series 9, Franco Ucci speaks with Kevin Lazarz and Matt Howalik about LiveStacks on Oracle LiveLabs and a new approach to hands-on technology learning. Instead of beginning with individual product features, LiveStacks provides fully configured applications that let learners experience an industry scenario and its business outcomes before exploring how the underlying architecture works.
Kevin and Matt explain how LiveStacks complements the hundreds of technical workshops already available through Oracle LiveLabs. Learners can begin with a working application, understand the use case, and then explore the technologies that make it possible. The discussion covers examples including AI lakehouse architectures, real-time data ingestion, change data capture, medallion architecture, vector search, JSON, property graphs, and AI capabilities within Oracle AI Database 26ai.
The conversation also explores Select AI, Select AI agents, natural language interaction with data, embedded AI models, and private AI services. Kevin and Matt explain how learners can deploy LiveStacks into their own environments, modify the applications, connect them with AI agents, and then use LiveLabs workshops to understand individual capabilities in greater depth. The result is a practical learning journey that connects real-world applications and business outcomes with the architecture and technologies behind them.

Jason Reinhardt explains how Oracle Live AI Hub uses Autonomous AI Database to connect data across relational databases, files, lakehouses, and clouds for AI-powered analysis and application development. The approach helps organizations work with distributed data where it resides while providing the flexibility to replicate data when performance requirements make that beneficial.

In this episode of Digital Impact Radio Series 9, Franco Ucci speaks with Jason Reinhardt about Oracle Live AI Hub, a solution pattern built on Autonomous AI Database that connects data from multiple sources and makes it available for AI, analytics, and application development. Jason explains how organizations can connect Oracle and non-Oracle databases, relational and unstructured data, files, lakehouse technologies, and data across different clouds without automatically having to move or replicate that data.

The conversation explores how managed connectors can provide access to sources including PostgreSQL, SQL Server, DB2, Snowflake, Databricks, and Apache Iceberg, while organizations can still choose replication technologies when performance requirements call for them. Jason also discusses how the Live AI Hub can support everything from data analysis to polyglot applications, combining relational data, JSON, spatial data, vectors, large language models, and AI agent frameworks through a common database foundation.

Franco and Jason examine how this approach can simplify access to distributed enterprise data while supporting applications built with technologies such as Python and Node.js. They also discuss the role of Autonomous AI Database in providing a managed foundation that can scale from small experiments to larger applications, along with ways developers can get hands-on experience through Oracle Free Tier, developer editions, LiveLabs, and Live Stacks.