We want to use IRIS as a backend for a lightweight blockchain or DLT. Can we model blocks using deterministic globals and implement consensus (PBFT, Raft) externally while using IRIS as the ledger?

We’re ingesting high-volume HL7 messages and converting them to FHIR in near-real-time. How do we design a streaming ETL pipeline using interoperability (productions) that scales horizontally?

I am trying to add Plotly Bar graph in a div to a CSPpage. I am working in IRIS 2022.1. I created persistent class.

I copied relevant code into github repo:

oliverwilms/iris-python-plotly

iris-python-plotly/csp/otwPlotly.csp at master · oliverwilms/iris-python-plotly

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.

The built-in %JSONExport() fails with circular references in deeply nested objects. How can I write a custom serializer that supports circular detection and reference tracking?

Some languages ​​have the concept of a garbage collector for automatic memory management. I'd like to know if something like this exists in InterSystems Caché in the context of routines, %CSP.REST, or %CSP.Page.

The question arises from the %Close() method of the %RegisteredObject class. This indicates that I need to manually clear the object from memory if it's no longer in use, or in the web context, if the request has completed. Is this correct? Or am I completely wrong?

Thank you!

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.

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.

We are happy to present the bonuses page for the applications submitted to the InterSystems .Net, Java, Python, and JavaScript Contest!

See the results below.

This anthropic article made me think of several InterSystems presentations and articles on the topic of data quality for AI applications. InterSystems is right that data quality is crucial for AI, but I imagined there would be room for small errors, but this study suggests otherwise. That small errors can lead to big hallucinations. What do you think of this? And how can InterSystems technology help?

https://www.anthropic.com/research/small-samples-poison

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.

Can the IRIS SQL engine be extended with custom optimization rules (e.g., prioritizing certain indices or join orders)? If not, is there a supported way to influence cost models?

I’m using recursive CTEs for hierarchical data, but the planner seems to produce inefficient plans. Can I influence or extend the query optimizer behavior in IRIS?

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.

This code provide the configured production items with enabled or disabled status.

Include (Ensemble, EnsUI, EnsUtil)

Class Test.ProductionConfig
{