As part of improvements regarding CCR usage and usability, certain transitions are now blocked when a CCR Record has undeployed ItemSets for required Environments.

Hola amigo! 😊 Cómo estás hoy,

I would like to share a small part of my learnings from my first ever official project: POS/EDC machine integration with our billing system. This was an exciting challenge where I got hands-on experience working with APIs and vendors.

How does a Payment Machine actually work?

It's simple, start by initiating/creating a transaction, then retrieve its payment status.

Here, initiate/create refers to POST method and Retrieve refers to GET.

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:

Chasing errors or misbehavior in the network can be quite a challenge.
Differently to a local application on the DB server, you always have at least 3 players:

• A client to place a request
• some kind of transport layer
• and a server to provide a reply.

This results in a minimum of 3 possible communication layers

FastJsonSchema: High-Performance JSON Validation in IRIS

Validating JSON data against JSON Schema is a common requirement for modern applications. FastJsonSchema brings this capability natively to InterSystems IRIS, combining speed, simplicity, and full schema compliance.

Unlike traditional validation approaches, FastJsonSchema generates native ObjectScript code from your JSON Schemas and compiles it directly to iris object code, enabling idiomatic performance without relying on external libraries or runtimes.

When I started my journey with InterSystems IRIS, especially in Interoperability, one of the initial and common questions I had was: how can I run something on an interval or schedule? In this topic, I want to share two simple classes that address this issue. I'm surprised that some similar classes are not located somewhere in EnsLib. Or maybe I didn't search well? Anyway, this topic is not meant to be complex work, just a couple of snippets for beginners.

InterSystems FAQ rubric

When exporting using the Export() method of the %Library.Global class, if the export format (fourth argument: OutputFormat) is set to 7, "Block format/Caché block format (%GOF)," mapped globals cannot be exported (only globals in the default global database of the namespace are exported). To export mapped globals in "Block format/Caché block format (%GOF)," specify the database directory to which you want to map them in the first parameter of %Library.Global.Export().

An example of execution is shown below.

When I was younger (a question about exactly how much younger is outside the scope of this article), the word “token” meant fun. You see, just a couple of times a year, I would get to go to an arcade and play some amusing video games with my friends.

InterSystems IRIS Community Edition HAOS Add-On

Run InterSystems IRIS inside of Home Assistant, as an add-on. Before you dismiss this article possibly under the guise that this is just a gimmick, Id like you to step back and take a look at how easy it is to launch IRIS based applications using this platform. If you look at Open Exchange, you will see dozens of dozens of applications worthy of launching while they are basically hung out to dry as gitware, and launchable if you want to get into a laptop battle with containerd or Docker. With a simple git repo, and a specification, you can now build your app on IRIS, and make it launchable through a marketplace with limited hassle to your end users. Run it along side Ollama and the LLM/LAM implementations, expose anything in IRIS as a sensor or expose an endpoint for interaction in your IRIS app to interact with anything you've connected to HAOS. Wanna restart an IRIS production with a flick of a physical switch or Assisted AI? You can do it with this add-on, or your own, right alongside the home automation hackers.

Hi all,

This is a quick tip about how to use case insensitive URL in REST API.

If you have a class that extends from %CSP.REST and Ens.BusinessService, to create a REST API service, and you have defined your WebApplication in lowercase

Introduction

Businesses often use in-memory databases or key-value stores (caching layers) when applications require extremely high performance. However, in-memory databases incur a high total cost of ownership and have hard scalability limits, incurring reliability problems and restart delays when memory limits are exceeded. In-memory key-value stores share these limitations and introduce architectural complexity and network latency as well.

This article explains why InterSystems IRIS™ data platform is a superior alternative to in-memory databases and key-value stores for highperformance SQL and NoSQL applications.

Taking Performance and Efficiency to the Next Level

InterSystems IRIS is the only persistent database that can match or beat the performance of in-memory databases and caching layers for concurrent data ingestion and analytics processing. It can process incoming transactions, persist the data to disk, and index it for analytics in under one microsecond on commercially available hardware without introducing network latency.

The superior ingest performance of InterSystems IRIS results in part from its multi-dimensional data engine, which allows efficient and compact storage in a rich data structure. Using an efficient, multi-dimensional data model with sparse storage techniques instead of two-dimensional tables, random data access and updates are accomplished with very high performance, fewer resources and less disk capacity. It also provides in-memory, in-process APIs in addition to traditional TCP/IP access APIs to optimize ingest performance.

If you start with InterSystems ObjectScript, you will meet the XECUTE command.
And beginners may ask: Where and Why may I need to use this ?

The official documentation has a rich collection of code snippets. No practical case.
Just recently, I met a use case that I'd like to share with you.

Kamino for IrisClusters

If you are in the business of building a robust High Availability, Disaster Recovery or Stamping multiple environments rapidly and in a consistent manner Karmada may just be the engine powering your Cloning Facility.