Introduction

The InterSystems IRIS Data Platform has long been known for its performance, interoperability, and flexibility across programming languages. For years, developers could use IRIS with Python, Java, JavaScript, and .NET — but Go (or Golang) developers were left waiting.

Golang Logo

That wait is finally over.

The new go-irisnative driver brings GoLang support to InterSystems IRIS, implementing the standard database/sql API. This means Go developers can now use familiar database tooling, connection pooling, and query interfaces to build applications powered by IRIS.


Why GoLang Support Matters

GoLang is a language designed for simplicity, concurrency, and performance — ideal for cloud-native and microservices-based architectures. It powers some of the world’s most scalable systems, including Kubernetes, Docker, and Terraform.

Bringing IRIS into the Go ecosystem enables:

  • Lightweight, high-performance services using IRIS as the backend.
  • Native concurrency for parallel query execution or background processing.
  • Seamless integration with containerized and distributed systems.
  • Idiomatic database access through Go’s database/sql interface.

This integration makes IRIS a perfect fit for modern, cloud-ready Go applications.

7 8
0 138

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?

10 7
3 153

Table of Contents

  1. Purpose of the article
  2. What containers are and why they make sense with IRIS
     2.1 Containers and images in a nutshell
     2.2 Why containers are useful for developers
     2.3 Why IRIS works well with Docker
  3. Prerequisites
  4. Installing the InterSystems IRIS image
     4.1 Using Docker Hub
     4.2 Pulling the image
  5. Running the InterSystems IRIS image
     5.1 Starting an IRIS container
     5.2 Checking container status
     5.3 Executing code in the container terminal
     5.4 Accessing the IRIS Management Portal
     5.5 Connecting the container to VS Code
     5.6 Stopping or removing the container
     5.7 Setting a specific password with a bind mount
     5.8 Using durable %SYS volumes
      5.8.1 What gets stored with durable %SYS
      5.8.2 How to enable durable %SYS
  6. Using Docker Compose
     6.1 Docker Compose example
     6.2 Running Docker Compose
  7. Using a Dockerfile to run custom source code
     7.1 Dockerfile example
     7.2 Docker Compose example
     7.3 Understanding layers, image tagging and build vs. run time
     7.4 Source code and init script
     7.5 Building the image with Dockerfile
     7.6 Running instructions in the containerized IRIS terminal
  8. Conclusion and what’s next

12 4
5 151

Hello!!!

Data migration often sounds like a simple "move data from A to B task" until you actually do it. In reality, it is a complex process that blends planning, validation, testing, and technical precision.

Over several projects where I handled data migration into a HIS which runs on IRIS (TrakCare), I realized that success comes from a mix of discipline and automation.

Here are a few points which I want to highlight.

1. Start with a Defined Data Format.

Before you even open your first file, make sure everyone, especially data providers, clearly understands the exact data format you expect. Defining templates early avoids unnecessary bank-and-forth and rework later.

While Excel or CSV formats are common, I personally feel using a tab-delimited text file (.txt) for data upload is best. It's lightweight, consistent, and avoids issues with commas inside text fields.

PatID   DOB Gender  AdmDate
10001   2000-01-02  M   2025-10-01
10002   1998-01-05  F   2025-10-05
10005   1980-08-23  M   2025-10-15

Make sure that the date formats given in the file is correct and constant throughout the file because all these files are usually converted from an Excel file and an Basic excel user might make mistakes while giving you the date formats wrong. Wrong date formats can irritate you while converting into horolog.

2 8
1 62

I am truly excited to continue my "InterSystems for Dummies" series of articles, and today, we want to tell you everything about one of the most powerful features we have for interoperability.

Hey, even if you have already had a go, we plan to take a really close look at how to get the most out of them and make our production even better.

12 2
5 173

gj :: configExplorer is a new VS Code extension integrating with Server Manager and leveraging Structurizr to produce configuration diagrams of your servers.

Here's a short introductory video.

https://www.youtube.com/embed/WHkoZsg6P-A
[This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]

2 6
0 87
Article
· Oct 22 2m read
Tips on handling Large data

Hello community,

I wanted to share my experience about working on Large Data projects. Over the years, I have had the opportunity to handle massive patient data, payor data and transactional logs while working in an hospital industry. I have had the chance to build huge reports which had to be written using advanced logics fetching data across multiple tables whose indexing was not helping me write efficient code.

Here is what I have learned about managing large data efficiently.

Choosing the right data access method.

As we all here in the community are aware of, IRIS provides multiple ways to access data. Choosing the right method, depends on the requirement.

  • Direct Global Access: Fastest for bulk read/write operations. For example, if i have to traverse through indexes and fetch patient data, I can loop through the globals to process millions of records. This will save a lot of time.
Set ToDate=+H
Set FromDate=+$H-1 For  Set FromDate=$O(^PatientD("Date",FromDate)) Quit:FromDate>ToDate  Do
. Set PatId="" For  Set PatId=$Order(^PatientD("Date",FromDate,PatID)) Quit:PatId=""  Do
. . Write $Get(^PatientD("Date",FromDate,PatID)),!
  • Using SQL: Useful for reporting or analytical requirements, though slower for huge data sets.

2 6
1 56

If you thought native Go support for IRIS was exciting, wait until you see what happens when GORM enters the mix.


Just recently, we welcomed native GoLang support for InterSystems IRIS with the release of go-irisnative. That was just the beginning. Now, we’re kicking things up a notch with the launch of gorm-iris — a GORM driver designed to bring the power of Object Relational Mapping (ORM) to your IRIS + Go stack.

Why GORM?

GORM is one of the most popular ORM libraries in the Go ecosystem. It makes it easy to interact with databases using Go structs instead of writing raw SQL. With features like auto migrations, associations, and query building, GORM simplifies backend development significantly.

So naturally, the next step after enabling Go to talk natively with IRIS was to make GORM work seamlessly with it. That’s exactly what gorm-iris does.

5 4
1 76

I know the next ones:

1. Place all different settings in environment variables. You have a different .env file for each environment, and you must add some code to Production for reading and setting these values. It's good for deploying into containers, but challenging for management when we have a large production. I mean, we have many settings that can vary depending on the environment: active flag, pool size, timeouts, and so on. Not only endpoints.

1 10
0 114

Hi,

It's me again😁, recently I am working on generating some fake patient data for testing purpose with the help of Chat-GPT by using Python. And, at the same time I would like to share my learning curve.😑

1st of all for building a custom REST api service is easy by extending the %CSP.REST

Creating a REST Service Manually

Let's Start !😂

3 3
1 57

I am working on a tool that configures an instance to use a common default routine database across all custom Namespaces. For instances that already have distinct default routine databases for their Namespaces, this would involve a step of merging over all code from the current default routine databases to the new "super" routine database. This should be done in such a way that only merges contents in the default routine database (not mapped databases) and is able to detect/exclude contents that already exist in the target database.

1 11
0 105

In my previous article, Using LIKE with Variables and Patterns in SQL, we explored how the LIKE predicate behaves in different scenarios, from Embedded SQL to Dynamic SQL, and what happens to performance when wildcards and variables come into play. That piece was about getting comfortable writing a working LIKE query. But writing SQL that works is only the starting point. To build applications that are reliable, scalable, and secure, you need to understand the best practices that underpin all SQL, including queries that use LIKE.

This article takes the next step. We’ll look at a few key points to help strengthen your SQL code, avoid common pitfalls, and make sure your SELECT statements run not just correctly, but also efficiently and safely. I'll use SELECT statements with LIKE predicate as an example along the way, showing how these broader principles directly affect your queries and their results.

*This is what Gemini came up with for this article, kinda cute.

7 0
0 107

InterSystems IRIS Data Platform is a comprehensive, multi-model, multi-workload data platform that is ideal for accommodating the challenging requirements of applications for the Internet of Things. It is a complete platform for developing, executing, and maintaining IoT applications in a single, consistent, unified environment. It features a distributed architecture to support massive data-ingest rates and data volumes, while providing the flexibility and durability of an enterprise-grade transactional multi-model database to ingest, process, and persist data from a wide range of devices in different formats. It features a complete set of integration, event-processing, and integrated analytics capabilities, including full SQL support and text processing, business process orchestration, and a standards-based development environment.

Connect to, ingest, and persist a wide range of disparate device data types and formats

The data types associated with IoT applications are often heterogeneous, as they may originate from various devices with diverse functions and manufactured by different vendors. The underlying data platform must be able to ingest and process a wide range of raw data types in their original formats. Many applications also require the data platform to persist all of the disparate source data to detect deviations from normal ranges, accommodate downstream ad hoc analytics, maintain regulatory compliance, and fulfill other purposes.

5 0
1 107
3 2
0 59

Deploying new IRIS instances can be a time-consuming task, especially when setting up multiple environments with mirrored configurations.

I’ve encountered this issue many times and want to share my experience and recommendations for using Ansible to streamline the IRIS installation process. My approach also includes handling additional tasks typically performed before and after installing IRIS.

3 2
3 54

Since we reached two important milestones for Go developers working with InterSystems IRIS:

Now it’s time to see everything working together.

To demonstrate how easily Go developers can adopt InterSystems IRIS, I took an existing production-grade open-source project — the RealWorld Example App — which showcases a full-stack Medium.com-style clone implemented with Go Fiber, GORM, and SQLite.

RealWorld Example App

With just a few configuration tweaks, I swapped out SQLite for gorm-iris, keeping everything else unchanged. The result?
A fully functional Go + Fiber application powered by InterSystems IRIS — no code rewrites, no ORM gymnastics, just a different database backend.

You can find the complete working demo here: github.com/caretdev/golang-fiber-iris-realworld-example-app

4 1
1 53

The ObjectScript language has incredible JSON support through classes like %DynamicObject and %JSON.Adaptor. This support is due to the JSON format's immense popularity over the previous dominance of XML. JSON brought less verbosity to data representation and increased readability for humans who needed to interpret JSON content. To further reduce verbosity and increase readability, the YAML format was created. The very easy-to-read YAML format quickly became the most popular format for representing configurations and parameterizations, due to its readability and minimal verbosity.

4 1
1 46

Hey Community,

Enjoy the new video on InterSystems Developers YouTube:

InterSystems Different by Design @ Ready 2025

https://www.youtube.com/embed/TdEperSTNlA
[This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]

2 1
0 45

Hi Team,

Can I please check if anyone has built a simple web interface for maintaining custom SQL lookup class.

We have a simple persistent class in HealthShare which is used for storing Pathology test codes. Test codes in this lookup class is used for message filtering and applying additional logic when processing pathology results/orders.

0 2
0 60

Can someone help me understand what type of user error (?) is going on here please?

One one system, I write out a group of $c() values and get the expected results:

USER>for i=250:1:260 { write i," ", $c(i),! }
250 ú
251 û
252 ü
253 ý
254 þ
255 ÿ
256 Ā
257 ā
258 Ă
259 ă
260 Ą

USER>w $zv
IRIS for Windows (x86-64) 2023.1.4 (Build 580U) Fri Apr 19 2024 11:16:07 EDT
USER>

On another system, I get some unexpected results:

2 3
1 58

With the rapid adoption of telemedicine, remote consultations, and digital dictation, healthcare professionals are communicating more through voice than ever before. Patients engaging in virtual conversations generate vast amounts of unstructured audio data, so how can clinicians or administrators search and extract information from hours of voice recordings?

0 1
0 40

Hi all,

Let's do some more work about the testing data generation and export the result by REST API.😁

Here, I would like to reuse the datagen.restservice class which built in the pervious article Writing a REST api service for exporting the generated patient data in .csv

This time, we are planning to generate a FHIR bundle include multiple resources for testing the FHIR repository.

2 1
0 38