When we create a FHIR repository in IRIS, we have an endpoint to access information, create new resources, etc. But there are some resources in FHIR that probably we wont have in our repository, for example, Binary resource (this resource returns a document, like PDF for example).

I have created an example that when a Binary resource is requested, FHIR endpoint returns a response, like it exists in the repository. 

Monitoring your IRIS deployment is crucial. With the deprecation of System Alert and Monitoring (SAM), a modern, scalable solution is necessary for real-time insights, early issue detection, and operational efficiency. This guide covers setting up Prometheus and Grafana in Kubernetes to monitor InterSystems IRIS effectively. 

This guide assumes you already have an IRIS cluster deployed using the InterSystems Kubernetes Operator (IKO), which simplifies deployment, integration and mangement.

After so many years of waiting, we finally got an official driver available on Pypi

Additionally, found JDBC driver finally available on Maven already for 3 months,  and .Net driver on Nuget more than a month.

 As an author of so many implementations of IRIS support for various Python libraries, I wanted to check it. Implementation of DB-API means that it should be replaceable and at least functions defined in the standard. The only difference should be in SQL.

And the beauty of using already existing libraries, that they already implemented other databases by using DB-API standard, and these libraries already expect how driver should work.

I decided to test InterSystems official driver by implementing its support in SQLAlchemy-iris library.

Motivation

I started programming back in 2015, when I was doing my bachelor's in computer science. I didn't know about ObjectScript until I started my new job four months ago. Objectscript isn't actually a young programming language. Compared to C++, Java and Python, the community isn't as active, but we're keen to make this place more vibrant, aren't we?

Using SQL Gateway with Python, Vector Search, and Interoperability in InterSystems Iris

Part 3 – REST and Interoperability

Now that we have finished the configuration of the SQL Gateway and we have been able to access the data from the external database via python, and we have set up our vectorized base, we can perform some queries. For this in this part of the article we will use an application developed with CSP, HTML and Javascript that will access an integration in Iris, which then performs the search for data similarity, sends it to LLM and finally returns the generated SQL. The CSP page calls an API in Iris that receives the data to be used in the query, calling the integration. For more information about REST in the Iris see the documentation available at https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls...

Introduction

To achieve optimized AI performance, robust explainability, adaptability, and efficiency in healthcare solutions, InterSystems IRIS serves as the core foundation for a project within the x-rAI multi-agentic framework. This article provides an in-depth look at how InterSystems IRIS empowers the development of a real-time health data analytics platform, enabling advanced analytics and actionable insights. The solution leverages the strengths of InterSystems IRIS, including dynamic SQL, native vector search capabilities, distributed caching (ECP), and FHIR interoperability. This innovative approach directly aligns with the contest themes of "Using Dynamic SQL & Embedded SQL," "GenAI, Vector Search," and "FHIR, EHR," showcasing a practical application of InterSystems IRIS in a critical healthcare context.

Using Flask, REST API, and IAM with InterSystems IRIS

Part 1 - REST API

Hello

In this article we will see the implementation of a REST API to perform the maintenance of a CRUD, using Flask and IAM.

In this first part of the article we will see the construction and publication of the REST API in Iris.

First, let's create our persistent class to store the data. To do this, we go to Iris and create our class:

What is TLS?

TLS, the successor to SSL, stands for Transport Layer Security and provides security (i.e. encryption and authentication) over a TCP/IP connection. If you have ever noticed the "s" on "https" URLs, you have recognized an HTTP connection "secured" by SSL/TLS. In the past, only login/authorization pages on the web would use TLS, but in today's hostile internet environment, best practice indicates that we should secure all connections with TLS.

Parallel query hinting boosts certain query performances on multi-processor systems via parallel processing. The SQL optimizer determines when this is beneficial. On single-processor systems, this hint has no effect.

Parallel processing can be managed by:

1. Setting the auto parallel option system-wide.
2. Using the %PARALLEL keyword in the FROM clause of specific queries.

%PARALLEL is ignored when it applied to:

Host Variables are a rather common programming feature in many implementations of SQL. 
A recent question in DC made me aware that in IRIS, Caché, Ensemble, ... 
host variables just exist within embedded SQL

>  You can supply host variables for Embedded SQL queries only. <

Related examples are included in the available Documentation

This is a description  for a workaround if you don't / can't use embedded SQL.

InterSystems OMOP, The Cloud Service (Troy)

Overview

With the help of SQL, you can build, train, and manage machine learning models directly in the database with InterSystems IRIS's robust IntegratedML tool. Using SQL examples that represent your data, we will go over IntegratedML configuration and how it is used in practical situations in this article.

Using SQL Gateway with Python, Vector Search, and Interoperability in InterSystems Iris

Part 1 - SQL Gateway

Hello

In this article we will look at the use of SQL Gateway in Iris. SQL Gateway allows Iris to have access to tables from other (external) database via ODBC or JDBC. We can access Tables or Views from various databases, such as Oracle, PostgreSQL, SQL Server, MySQL and others.

Using SQL Gateway with Python, Vector Search, and Interoperability in InterSystems Iris

Part 2 – Python and Vector Search

Since we have access to the data from our external table, we can use everything that Iris has to offer with this data. Let's, for example, read the data from our external table and generate a polynomial regression with it.

For more information on using python with Iris, see the documentation available at https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls?KEY=AFL_epython

Let's now consume the data from the external database to calculate a polynomial regression. To do this, we will use a python code to run a SQL that will read our MySQL table and turn it into a pandas dataframe:

Hey, community! 👋

We are a team of Stanford students applying technology to make sense of climate action. AI excites us because we know we can quickly analyze huge amounts of text.

As we require more reports on sustainability, such as responsibility reports and financial statements, it can be challenging to cut through the noise of aspirations and get to the real action: what are companies doing

That’s why we built a tool to match companies with climate actions scraped from company sustainability reports.

Introduction

A REST API (Representational State Transfer) is an interface that allows different applications to communicate with each other through the HTTP protocol, using standard operations such as GET, POST, PUT, and DELETE. REST APIs are widely used in software development to expose services accessible by other applications, enabling integration between different systems.

Hello

This article follows up on the question I had asked the community UDP Adapter not working

In this article, I will present to you
1) What is "UDP"?
2) The current state of Iris with UDP
3) My solution with the UDP adapter

Submission for InterSystems Technical Article Contest 2025

By Suze van Adrichem, Alice Heiman and Bubble Yu

View our video here: https://share.descript.com/view/JjI5tob8La

From the previous article, we identified some issues when working with JSON in SQL.

IRIS offers a dedicated feature for handling JSON documents, called DocDB.

InterSystems IRIS® data platform DocDB is a facility for storing and retrieving database data. It is compatible with, but separate from, traditional SQL table and field (class and property) data storage and retrieval. It is based on JSON (JavaScript Object Notation) which provides support for web-based data exchange. InterSystems IRIS provides support for developing DocDB databases and applications in REST and in ObjectScript, as well as providing SQL support for creating or querying DocDB data.

By its nature, InterSystems IRIS Document Database is a schema-less data structure. That means that each document has its own structure, which may differ from other documents in the same database. This has several benefits when compared with SQL, which requires a pre-defined data structure.

The word “document” is used here as a specific industry-wide technical term, as a dynamic data storage structure. “Document”, as used in DocDB, should not be confused with a text document, or with documentation.

Let's explore how DocDB can help store JSON in the database and integrate it into projects that rely solely on xDBC protocols.

FHIR repositories, applications and servers typically serve clinical data in small quantities, whether to return data about a patient, their medications, vaccines, allergies, among other information. However, it is common for a large amount of data in FHIR/JSON format to be requested to be used to load into Data Lakes, identifying study cohorts, population health, or transferring data from one EHR to another. To meet these business scenarios that require large extractions and loads of data, it is recommended to use the FHIR Bulk Data Access feature provided by HL7 institution.

Hi Community, 

In this article, we will explore the concepts of Dynamic SQL and Embedded SQL within the context of InterSystems IRIS, provide practical examples, and examine their differences to help you understand how to leverage them in your applications.

InterSystems SQL provides a full set of standard relational features, including the ability to define table schema, execute queries, and define and execute stored procedures. You can execute InterSystems SQL interactively from the Management Portal or programmatically using a SQL shell interface. Embedded SQL enables you to embed SQL statements in your ObjectScript code, while Dynamic SQL enables you to execute dynamic SQL statements from ObjectScript at runtime. While static SQL queries offer predictable performance, dynamic and embedded SQL offer flexibility and integration, respectively.

What is JWT?

JWT (JSON Web Token) is an open standard (RFC 7519) that offers a lightweight, compact, and self-contained method for securely transmitting information between two parties. It is commonly used in web applications for authentication, authorization, and information exchange.

A JWT is typically composed of three parts:

1. JOSE (JSON Object Signing and Encryption) Header
2. Payload
3. Signature

Introduction

What's in a name? That which we call a rose
By any other name would smell as sweet

William Shakespeare, "Romeo & Juliet"

In this article, we will describe a set of naming conventions for ObjectScript code.

Using Flask, REST API, and IAM with InterSystems IRIS

Part 2 – Flask App

Flask is a web development microframework written in Python. It is known for being simple, flexible, and enabling rapid application development.

Installing Flask is very simple. Once you have python installed correctly on your operating system, we need to install the flask library with the pip command. For REST API consumption, it is advisable to use the requests library. The following link provides a guide to installing flask: https://flask.palletsprojects.com/en/stable/installation/

Using Flask, REST API, and IAM with InterSystems IRIS

Part 3 – IAM

InterSystems API Manager (IAM) is a component that allows you to monitor, control, and manage traffic from HTTP-based APIs. It also acts as an API gateway between InterSystems IRIS applications and servers.

HTTP and HTTPS with REST API

Hello

The HTTP protocol allows you to obtain resources, such as HTML documents. It is the basis of any data exchange on the Web and a client-server protocol, meaning that requests are initiated by the recipient, usually a Web browser.

REST APIs take advantage of this protocol to exchange messages between client and server. This makes REST APIs fast, lightweight, and flexible. REST APIs use the HTTP verbs GET, POST, PUT, DELETE, and others to indicate the actions they want to perform.

When we make a call to a RESt API, what actually happens is an HTTP call. The API receives this call and according to the requested verb and path, the API performs the desired action. In the case of the Iris implementation we can see this clearly in the URLMap definition area:

REST API with Swagger in InterSystems IRIS

Hello

The HTTP protocol allows you to obtain resources, such as HTML documents. It is the basis of any data exchange on the Web and a client-server protocol, meaning that requests are initiated by the recipient, usually a Web browser.

REST APIs take advantage of this protocol to exchange messages between client and server. This makes REST APIs fast, lightweight, and flexible. REST APIs use the HTTP verbs GET, POST, PUT, DELETE, and others to indicate the actions they want to perform.

Introduction

In today's rapidly evolving threat landscape, organizations deploying mission-critical applications must implement robust security architectures that protect sensitive data while maintaining high availability and performance. This is especially crucial for enterprises utilizing advanced database management systems like InterSystems IRIS, which often powers applications handling highly sensitive healthcare, financial, or personal data.

You may encounter errors during any point of program execution, and there are several ways to raise and handle these exceptions. In this article, we'll explore how exceptions are handled efficiently in IRIS.

One of the most commonly used return types is %Status, which is used by methods to indicate success or failure. Let's begin by discussing %Status values.

Working with %Status

In this article, exceptions are covered.

Working with Exceptions

Instead of returning a %Status response, you can raise and throw an Exception. You are then responsible for catching the exception and validating it. IRIS provides five main classes to handle exceptions effectively. Additionally, you can create custom exception class definition based on your needs.

High-Performance Message Searching in Health Connect

The Problem

Have you ever tried to do a search in Message Viewer on a busy interface and had the query time out? This can become quite a problem as the amount of data increases. For context, the instance of Health Connect I am working with does roughly 155 million Message Headers per day with 21 day message retention. To try and help with search performance, we extended the built-in SearchTable with commonly used fields in hopes that indexing these fields would result in faster query times. Despite this, we still couldn't get some of these queries to finish at all.

Hades DatabaseConnector 6.4.0 now does IRIS stuff!

Professional Grade FHIR® to OMOP Transformation

No Code Text to SQL w/ Databricks Genie and InterSystems OMOP

Introduction

My guess is that most IRIS developers create their applications using its native ObjectScript language or, if using an external language, then most likely using either Java, Python or perhaps C++.

I suspect that only a minority have considered using JavaScript as their language of choice, which, if true, is a great shame, because, In my opinion and experience, JavaScript is the closest equivalent to ObjectScript in terms of its ability to integrate with the IRIS's underlying multi-dimensional database. 

Background:

This guideline provides an overview of how to design and implement a REST API interface for querying patient demographic data from an Electronic Patient Record (EPR) system using HealthConnect. The process involves sending a query request with the patient's identification number, retrieving the response from the EPR system, extracting the required patient demographic data from the HL7 message, and sending it as a JSON response to the supplier. The high-level process diagram is shown below (Screenshot 1).