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Hi Community,

On December 7, 2025, the InterSystems Developer Community officially celebrated its 10th anniversary! 🥳🎉

And now we honor this decade of learning, collaboration, problem-solving, and advancing InterSystems technologies. Whether you’ve been here since the beginning or joined recently, thank you for your contributions, questions, ideas, and support. This milestone belongs to all of you 💖 You’ve built this community into what it is today, and we’re truly grateful!

As part of the celebration, we invited you to participate in a special anniversary video. And boy, you delivered! Thank you to everyone who took the time to share their greetings, memories, and kind words.

https://www.youtube.com/embed/oYjP3a3u8Io
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Hi community!

I am excited to say that since the beginning of this year we have published many of the client SDKs for InterSystems IRIS, InterSystems IRIS for Health and Health Connect to the corresponding external repositories (Maven, NuGet, npm and PyPI). This provides many benefits to you such as:

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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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Every thriving technical community has individuals whose curiosity, perseverance, and generosity help shape its collective knowledge. In the InterSystems Developer Community, one such contributor is @Scott Roth, who has been an inspiring presence for nearly a decade.

👏 Let’s take a closer look at Scott's remarkable journey and his impact on the InterSystems ecosystem.

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Apache Airflow is the leading open-source platform to programmatically author, schedule, and monitor data pipelines and workflows using Python. Workflows are defined as code (DAGs), making them version-controlled, testable, and reusable. With a rich UI, 100+ built-in operators, dynamic task generation, and native support for cloud providers, Airflow powers ETL/ELT, ML pipelines, and batch jobs at companies like Airbnb, Netflix, and Spotify.

Airflow Application Layout

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Here are the technology bonuses for the InterSystems "Bringing Ideas to Reality" Contest 2025 that will give you extra points in the voting:

  • Developer Experience Idea implemented - 4
  • IRIS Vector Search usage -3
  • Embedded Python usage -3
  • InterSystems Interoperability - 3
  • InterSystems IRIS BI - 3
  • VSCode Plugin - 3
  • FHIR Tools - 3
  • Docker container usage -2
  • ZPM Package Deployment - 2
  • Online Demo -2
  • Find and report a bug - 2
  • Article on Developer Community - 2
  • The second article on Developer Community - 1
  • Video on YouTube - 3
  • YouTube Short - 1
  • First Time Contribution - 3

See the details below.<--break->

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Announcement
· Dec 2
Share your insights!

We value your feedback on the learning resources you use to get the most from InterSystems products. Whether you've taken self-paced or live courses, explored the documentation, or gotten certified, we'd love to hear from you!

How can InterSystems improve its learning resources in 2026? Take the survey.

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Hi Community,

In the first part of this series, we examined the fundamentals of Interoperability on Python (IoP), specifically how it enables us to construct such interoperability elements as business services, processes, and operations using pure Python.

Now, we are ready to take things a step further. Real-world integration scenarios extend beyond simple message handoffs.They involve scheduled polling, custom message structures, decision logic, filtering, and configuration handling.In this article, we will delve into these more advanced IoP capabilities and demonstrate how to create and run a more complex interoperability flow using only Python.

To make it practical, we will build a comprehensive example: The Reddit Post Analyzer Production. The concept is straightforward: continuously retrieving the latest submissions from a chosen subreddit, filtering them based on popularity, adding extra tags to them, and sending them off for storage or further analysis.

The ultimate goal here is a reliable, self-running data ingestion pipeline. All major parts (the Business Service, Business Process, and Business Operation) are implemented in Python, showcasing how to use IoP as a Python-first integration methodology.

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Hi Community,

With the General Availability of the 2025.3 release of InterSystems IRIS® data platform, InterSystems IRIS® for Health™, and HealthShare® Health Connect, we are now collecting your ideas for improvement.

If the new release inspired you or highlighted opportunities to enhance the developer experience, please share your suggestions on the InterSystems Ideas Portal - every idea is reviewed by our product teams and can influence future releases.

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Modern SQL engines are enormously complex pieces of software. Even when they appear stable and mature, subtle bugs can hide in their optimizers, type systems, predicate evaluation, or execution layers. These bugs rarely announce themselves loudly. Instead, they quietly produce incorrect results, behave inconsistently, or fail abruptly under specific combinations of SQL constructs.

This is precisely why tools like SQLancer exist. SQLancer automatically generates SQL queries and uses logical “oracles” to detect when a database behaves incorrectly. It has revealed hundreds of real bugs in widely used systems such as MySQL, PostgreSQL, SQLite, and DuckDB.

With this in mind, I attempted to bring SQLancer to InterSystems IRIS, starting with the NOREC oracle — a powerful method for detecting optimizer correctness issues. The journey, however, uncovered not just potential SQL correctness problems, but also a surprising number of driver-level and server-level failures that prevented SQLancer from running at full strength.

This article summarizes why SQLancer is important, how the NOREC oracle works, and what unexpected findings appeared while testing IRIS.

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The 2025.3 release of InterSystems IRIS® data platform, InterSystems IRIS® for Health, and HealthShare® Health Connect is now Generally Available (GA). This is a Continuous Delivery (CD) release.

Release Highlights:

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Modern data architectures utilize real-time data capture, transformation, movement, and loading solutions to build data lakes, analytical warehouses, and big data repositories. It enables the analysis of data from various sources without impacting the operations that use them. To achieve this, establishing a continuous, scalable, elastic, and robust data flow is essential. The most prevalent method for that is through the CDC (Change Data Capture) technique. CDC monitors for small data set production, automatically captures this data, and delivers it to one or more recipients, including analytical data repositories. The major benefit is the elimination of the D+1 delay in analysis, as data is detected at the source as soon as it is produced, and later is replicated to the destination.

This article will demonstrate the two most common data sources for CDC scenarios, both as a source and a destination. For the data source (origin), we will explore the CDC in SQL databases and CSV files. For the data destination, we will use a columnar database (a typical high-performance analytical database scenario) and a Kafka topic (a standard approach for streaming data to the cloud and/or to multiple real-time data consumers).

Overview

This article will provide a sample for the following interoperability scenario:

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Hi Community,

As part of our birthday celebration, we’ve put together a special timeline video showcasing the key milestones, growth, and achievements of the Developer Community and its Ecosystem over the past decade 🎆

Take a look at how far we’ve come, and how much we’ve built together:

https://www.youtube.com/embed/iZCfGAdWB2g
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As part of our 10th anniversary celebration, we invite you to take part in a discussion reflecting on your experience with the InterSystems Developer Community.

Over the past decade, thousands of members have shaped this space through knowledge sharing, collaboration, and meaningful connections — and your voice is an integral part of that history.

We encourage you to join the conversation and share your story. In the comments, please tell us:

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Hi Community!

Thank you to everyone who participated in the "Improving the Initial Developer Experience" sweepstakes! Your feedback is invaluable in making InterSystems products better, and we will use your ideas to improve our offerings. Now, it's time to announce the winner - watch the video to see the sweepstake drawing:

https://www.youtube.com/embed/d2ye_mnBxZo
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In the previous article, we talked about ODBC and connecting from C#. And now, let's look at JDBC and Java. The InterSystems JDBC driver is the recommended, high-performance way to integrate your Java applications.

Here is a step-by-step guide to getting your Java application connected to an IRIS instance using the JDBC driver.

Step 1: Obtain and Include the InterSystems IRIS JDBC Driver

Unlike ODBC drivers, which are often installed system-wide, JDBC drivers are typically distributed as JAR files that must be included in your Java project's classpath.

If InterSystems IRIS is installed on your local machine or another you have access to, you can find the file in install-dir/dev/java/lib/ or similar, where install-dir is the installation directory for the instance. Conversely, you can download the jar file from Driver packages page.

Or as suggested by @Dmitry Maslennikov in the comments, use the maven central repository for Maven:

<dependency>
    <groupId>com.intersystems</groupId>
    <artifactId>intersystems-jdbc</artifactId>
    <version>3.10.5</version>
</dependency>

or for Gradle:

implementation("com.intersystems:intersystems-jdbc:3.10.5")

Include the jar file in Project:

  • Maven/Gradle: If you use a build tool, the simplest method is to add the InterSystems JDBC driver as a dependency in your pom.xml or build.gradle file. This automatically downloads and manages the JAR.
  • Manual: For simple projects, you must place the JAR file in a project directory (e.g., /lib) and explicitly add it to your classpath when compiling and running.

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We are a group of interface analysts in a healthcare setting, running IRIS for Health 2024, having upgraded over time from an old ENSEMBLE environment. We have been working on a wish list of development goals, but are having trouble finding the correct, best practice method/path for getting to what we envision.

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In some cases, it's necessary to manipulate data from one namespace to another. For example, a routine in the "N1" namespace needs data from the "N2" namespace. In legacy systems (using only globals), it's common to make the global universal, but what about persistent classes? Is this type of globalization also possible?

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Hello!
I have the following XML document obtained through a string:

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<MainDocument xmlns="urn:hl7-org:v3">
<realmCode code="IT"/>
<title>kjbkjkjbkjb</title>
<effectiveTime value="20090905150716"/>
[.....other tags.....]
<versionNumber value="1"/>
<component>
<body>mhvjhjkvhj</body>
<component>
<section>content</section>
<ID>5</ID>

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