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.

Given a JSON schema at runtime, I want to programmatically create persistent classes with corresponding properties and indices. Is there a way to dynamically compile and load such classes?

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.

For geographically distributed nodes using async mirroring or ECP, how can I detect and resolve data conflicts manually (custom logic) while maintaining eventual consistency?

Instead of default storage classes, I want to implement my own SQL storage mapping for a persistent class (e.g., denormalized or sparse matrix structures). How do I define and manage custom storage definitions?

To manage the accumulation of production data, InterSystems IRIS enables users to manage the database size by periodically purging the data. This purge can apply to messages, logs, business processes, and managed alerts.

Please check the documentation for more details on the settings of the purge task:
https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls?KEY=EGMG_purge#EGMG_purge_settings

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.

Join our next in-person Developer Meetup in Boston to explore Security & AI for Developers and Startups.

This event is hosted at CIC Venture Cafe.

Talk 1: When Prompts Become Payloads
Speaker: Mark-David McLaughlin, Director, Corporate Security, InterSystems

Talk 2: Serial Offenses: Common Vulnerability Types
Speaker: Jonathan Sue-Ho, Senior Security Engineer, InterSystems

>> Register here

Introduction

In a previous article, I presented the IRIStool module, which seamlessly integrates the pandas Python library with the IRIS database. Now, I'm explaining how we can use IRIStool to leverage InterSystems IRIS as a foundation for intelligent, semantic search over healthcare data in FHIR format.

This article covers what I did to create the database for another of my projects, the FHIR Data Explorer. Both projects are candidates in the current InterSystems contest, so please vote for them if you find them useful.

You can find them at the Open Exchange:

• IRIStool and Data Manager
• FHIR Data Explorer

In this article we'll cover:

• Connecting to InterSystems IRIS database through Python
• Creating a FHIR-ready database schema
• Importing FHIR data with vector embeddings for semantic search

Hi everyone! 👋
I’m excited to share the project I’ve submitted to the current InterSystems .Net, Java, Python, and JavaScript Contest — it’s called IRIStool and Data Manager, and you can find it on the InterSystems Open Exchange and on my GitHub page.

In my previous article introducing gj :: configExplorer I flagged up how an apparent bug in the Windows elements of the Native API for Node.js means it's not currently available to run in VS Code on a Windows desktop.

Hi Guys,

I've created Business service with MQTT Inbound Adapter and here is my settings, BTW I'm using an IP with port not sure if it must be a url?

and this is my class:

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

• The Wait Is Over: Welcome GoLang Support for InterSystems IRIS — where we unveiled the new go-irisnative driver, providing a native database/sql interface for Go.
• GORM Meets InterSystems IRIS: Introducing gorm-iris — where we showed how to integrate IRIS with GORM, one of the most popular Go ORM libraries.

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.

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

Hi Guys,

I'm looking to setup an MQTT adapter that also acts as broker to connect directly to an MQTT clients, is there an IRIS adapter or client that can be used as Broker as well?

Thanks