TL;DR: This article demonstrates how to run GraphRAG-style hybrid retrieval—combining vector similarity, graph traversal, and full-text search—entirely within InterSystems IRIS using the iris-vector-graph package. We use a fraud detection scenario to show how graph patterns reveal what vector search alone would miss.

Why Fraud Detection Needs Graphs

Every year, businesses and consumers lose billions to fraud. In 2024 alone, consumers reported $12.5 billion lost—a 25% increase year over year. What makes modern fraud so difficult to detect is that fraudsters rarely work alone.

Graphical Display of Tables

Here we will document how you can get the results of your Data Collection to be displayed graphically. The output of your project will look like this:

Note that I am working on a local machine. If you are doing this on a server then be aware to use the correct IP address.

First, we will import the three classes from the that we are going to need (note that we will edit them later):

You can take the xml and import it to your system.

The spec will actually create the dispatch class and implementation template.

Globals as a Graph Data Structure in Python

How to use the IRIS Native API + Python to see globals as a Graph Network Chart.

Iris Globals

Reading the documentation these topics are related to globals:

• A global consists of a set of nodes (in some cases, only one node), identified by subscripts.
• Each node can contain a value.
• ObjectScript includes functions to iterate through the nodes of a global and quickly access values.
• A global is automatically stored in the database. When you assign a value to a node of a global variable, the data is written immediately to the database.

This article introduces InterSystems iKnow Entity Browser, a web application which allows to visualize extracted and organized text data mined from a large number of texts, powered by InterSystems iKnow technology, which is also known as InterSystems Text Analytics in InterSystems IRIS. Feel free to play with the demo of this tool or learn more about it on InterSystems Open Exchange.

I started the development of this project in late 2016. From now on, my iKnow Entity Browser is used around the world by those who use InterSystems technology in their stack and those who do text mining.

Interesting to see this latest ranking come to my attention:

http://db-engines.com/en/ranking/graph+dbms

Look what's ranked 16th.  Shame a decision was made to deprecate it 

Hi,

I would like to draw your attention on a recently published article, titled "A Quick Guide on How to Prevail in the Graph Database Arena", that has been posted also at LinkedIn Intersystems Caché has been referenced several times.

About the Ontodia library

First of all, I think we should provide some background information about Ontodia and Caché DBMS. Let’s start with a less known product, Ontodia. Ontodia is the result of a joint project of the ISST lab of the ITMO University and VISmart, a software development company specializing in the semantic web domain. The Ontodia service was created as a web application for visualizing linked data and ontologies. We created this service because we couldn’t find simple, accessible and efficient tools for convenient visualization of linked data.