Hi Community,

Please welcome @Henry Pereira as our new Moderator in the Developer Community Team! 🎉

As an active member, Henry has consistently shared valuable insights, supported fellow developers, and driven meaningful discussions across the Community. His deep expertise and collaborative spirit make him a perfect fit to help guide and grow our Developer Community.

Let's greet Henry with a round of applause and look at his bio!

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InterSystems Developer Community is a community of 25,759 amazing developers
We're a place where InterSystems IRIS programmers learn and share, stay up-to-date, grow together and have fun!
Learn more
Article
· Apr 1, 2025 1m read
How to get server/instance info

Hi all,

As part of the development an API to know what is the instance of IRIS is connected, I've found some methods to know information about the server that can help you.

Get the server name: $SYSTEM.INetInfo.LocalHostName()

Get the server IP: $SYSTEM.INetInfo.HostNameToAddr($SYSTEM.INetInfo.LocalHostName())

Get the instance name: $PIECE($SYSTEM,":",2)

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Article
· Feb 26, 2025 6m read
The Case for IRIS and JavaScript

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.

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Article
· May 12, 2025 7m read
An Overview of Database Degrade

Introduction

Hello! In this article, I will be discussing database degrade, a type of data integrity issue one can face when using IRIS. First, I will be going over a review of the structure of IRIS databases. I'll then discuss how database degrade can manifest and common causes of degrade issues. I'll then conclude with general tips we give our customers about how to prevent or prepare for database degrade issues.

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The "Ask Developer Community AI" tool is an excellent resource for studying for the certification. I asked it about each topic that will be covered in the test and the results are below.
Note: I classified each answer by the assertiveness that I consider as good, average and bad.

Note 2: The article has 4 parts, each one for an exam area.

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Here at InterSystems, we often deal with massive datasets of structured data. It’s not uncommon to see customers with tables spanning >100 fields and >1 billion rows, each table totaling hundred of GB of data. Now imagine joining two or three of these tables together, with a schema that wasn’t optimized for this specific use case. Just for fun, let’s say you have 10 years worth of EMR data from 20 different hospitals across your state, and you’ve been tasked with finding….

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Article
· Jun 18, 2025 2m read
Options for Python Devs + Poll!

I am writing this post primarily to gather an informal consensus on how developers are using Python in conjunction with IRIS, so please respond to the poll at the end of this article! In the body of the article, I'll give some background on each choice provided, as well as the advantages for each, but feel free to skim over it and just respond to the poll.

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Hi Community,

We’re excited to share a brand-new Instruqt tutorial:

🧑‍🏫 RAG using InterSystems IRIS Vector Search

This hands-on lab walks you through building a Retrieval Augmented Generation (RAG) AI chatbot powered by InterSystems IRIS Vector Search. You’ll see how vector search can be leveraged to deliver up-to-date and accurate responses, combining the strengths of IRIS with generative AI.

✨ Why try it?

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It's been a while since the new UI for Productions and DTL was published as a preview and I would like to know your opinions about it.

WARNING: This is a personal opinion, totally personal and not related with InterSystems Corporation.

I'm going to start with the Interoperabilty screen:

Production screen:

The style is sober and without frills, following the line of cloud services design, I like it.

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Introduction

Database performance has become a critical success factor in a modern application environment. Therefore identifying and optimizing the most resource-intensive SQL queries is essential for guaranteeing a smooth user experience and maintaining application stability.

This article will explore a quick approach to analyzing SQL query execution statistics on an InterSystems IRIS instance to identify areas for optimization within a macro-application.

Rather than focusing on real-time monitoring, we will set up a system that collects and analyzes statistics pre-calculated by IRIS once an hour. This approach, while not enabling instantaneous monitoring, offers an excellent compromise between the wealth of data available and the simplicity of implementation.

We will use Grafana for data visualization and analysis, InfluxDB for time series storage, and Telegraf for metrics collection. These tools, recognized for their power and flexibility, will allow us to obtain a clear and exploitable view.

More specifically, we will detail the configuration of Telegraf to retrieve statistics. We will also set up the integration with InfluxDB for data storage and analysis, and create customized dashboards in Grafana. This will help us quickly identify queries requiring special attention.

To facilitate the orchestration and deployment of these various components, we will employ Docker.

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My usecase is sorting and removing duplicates and getting count from a file that has json messages as a individual rows.

I am currently planning to use pandas for this purpose as its really fast. Below are the steps i am following

1) call a python function (called function) from IRIS classmethod(calling function)

2) the call python function will read the json file in a dataframe

3) perform sorting, dup removal, count in the dataframe

4) convert the dataframe into iris stream

5) return back the stream to iris calling function class method

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My main goal of this article was to prove the use of InterSystems IRIS for Health for REST FHIR interoperability between multiple applications. In this use case, some initiating application makes a REST call to IRIS for Health (which is merely a passthrough for REST calls) to retrieve FHIR data from an Oracle Health R4 FHIR repository. Ideally, it simplifies the syntax for calling the Oracle Health APIs.

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The most upvoted idea on the InterSystems Ideas Portal—garnering 74 votes—requests a lightweight version of IRIS. While the platform has grown into a powerful data engine, many projects require only its SQL database capabilities. This article demonstrates how to build an unofficial, compact IRIS Community Edition image focused solely on core database functionality, reducing the image size by over 80%.

⚠️ Disclaimer

This project produces an unofficial, experimental image of InterSystems IRIS Community Edition.

  • Not supported or endorsed by InterSystems.
  • Use at your own risk. The modifications remove core platform features and may break compatibility with tools, APIs, and expected behaviors.
  • No warranties or guarantees apply, including fitness for production use.
  • Intended only for educational and experimental purposes by advanced users.

Why a Lightweight IRIS?

While IRIS today includes rich functionality—interoperability, analytics, machine learning, system management, etc.—many projects only require its core SQL capabilities. The official Community Edition Docker image is approximately:

  • Disk usage: 3.5–3.8 GB
  • Compressed size: ~1.1 GB

IRIS Light reduces that to:

  • Disk usage: ~575–583 MB
  • Compressed size: ~144–148 MB

This makes it suitable for:

  • Microservice or containerized SQL use
  • CI pipelines with faster startup and pull
  • Horizontal scaling where full features are unnecessary

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When working with InterSystems IRIS, database developers and architects often face a critical decision: whether to use Dynamic SQL or Embedded SQL for querying and updating data. Both methods have their unique strengths and use cases, but understanding their performance implications is essential to making the right choice. Response time, a key metric in evaluating application performance, can vary significantly depending on the SQL approach used. Dynamic SQL offers flexibility, as queries can be constructed and executed at runtime, making it ideal for scenarios with unpredictable or highly variable query needs. Conversely, Embedded SQL emphasizes stability and efficiency by integrating SQL code directly into application logic, offering optimized response times for predefined query patterns.

In this article, I will explore the response times when using these two types of SQL and how they depend on different class structures and usage of parameters. So to do this, I'm going to use the following classes from the diagram:

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Are you familiar with SQL databases, but not familiar with IRIS? Then read on...

About a year ago I joined InterSystems, and that is how IRIS got on my radar. I've been using databases for over 40 years—much of that time for database vendors—and assumed IRIS would be largely the same as the other databases I knew. However I was surprised to find that IRIS is in several ways quite unlike other databases, often much better. With this, my first article in the Dev Community, I'll give a high-level overview of IRIS for people that are already familiar with the other databases such as Oracle, SQL Server, Snowflake, PostgeSQL, etc. I hope I can make things clearer and simpler for you and save you some time getting started.

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Hi colleagues!

Often, while developing a frontend app or any other communication vs REST API, it is worth having a Swagger UI - a test UI for the REST API that follows Open API 2.0 spec. Usually, it is quite a handful as it lets have quick manual tests vs REST API and its responses and the data inside.

Recently I've introduced the Swagger support to the InterSystems IRIS FHIR template for FHIR R4 API:

How to get it working.

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Dear Community,

As the 🎄 Festive Season 🎄 approaches, we’re excited to send our warmest wishes your way. May your holidays be filled with the joy of 🧑‍💻 learning, 🫂 connecting with fellow developers, and the thrill of new ideas and challenges waiting in the year ahead!

Looking back on 2025, we’re delighted to celebrate another year of remarkable achievements together with YOU, our incredible members:

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