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.

Hi everyone, on HealthShare Unified Care Record 2024.1.0 Build, we're using the Analytics section to create a dashboard containing a time chart showing a cumulative curve of the number of documents indexed in the registry for each documentSource of each repository.We tried the following steps: we created a cube whose dimensions are the CreationDate, SourceValue, and repositoryUniqueID of the HS_Registry.Document table; in the Analytics section, we created a pivot table that lists the document creation date on each row, along with as many columns as each repository's documentSources.

Hi everyone,

I am trying to create a treeMapChart in IRIS BI that will then be displayed on my DeepSeeWeb dashboard. In the IRIS BI User Portal, this is an example of what my treeMapChart looks like:

I know there is a huge amount of rectangles in this graphic - I care most about the common components (the largest boxes) but I still want all of the boxes to show. However, it projects to my DeepSeeWeb dashboard as the following: 

The labels do not show, even if I hover over the boxes.

We've recently made available a new version of InterSystems IRIS in the Vector Search Early Access Program, featuring a new Approximate Nearest Neighbor index based upon the Hierarchical Navigable Small World (HNSW) indexing algorithm. This addition allows for highly efficient, approximate nearest-neighbor searches over large vector datasets, dramatically improving query performance and scalability.

The HNSW algorithm is designed to optimize vector search for high-dimensional data by building a graph-based structure, making it faster to find approximate neighbors in large collections of

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.

Hello,

I work on a dashboard. I understand basic html. I like to draw two boxes in different colors on the background. There will be multiple small boxes inside or over the boxes in the background. I defined the large boxes as <div> and the smaller boxes also as <div> inside the larger <div>. So far so good.

How can I draw lines with arrows between the smaller boxes?

Each small box represents a process that gets a number in a circle and a status indicator: green = okay, red = not okay.

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. - You can see the

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.

Hello,

I started a post when I tried to display a line graph on a dashboard:

https://community.intersystems.com/post/dashboard-line-graph

This did not work very well. I switched gears and now I have a Zen Page that includes a Zen Report in iFrame. However my line chart does not display a line.

This is my Report class:

/// AETMON.Report
Class AETMON.Report Extends %ZEN.Report.reportPage
{
/// Class name of application this report belongs to.
Parameter APPLICATION;
/// Specifies the default display mode used for this report if
/// the URL parameter, <var>$MODE</var>, is not present.
Parameter DEFAULTMODE A

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. In the "Multi-model Database Engine" section of this article, there is a quick description of Caché  as an

object database with relational access, integrated support for JSON documents and a multidimensional key-value storage mechanism that can be easily extended to cover Graph data model

I believe strongly that Intersystems Caché is an exceptional database

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.

A typical use case for Ontodiа