I have experienced that my iris server is gone due to upgrading the docker version when I have built IRIS server on docker container.

Based on this experience, I'd like to show you how to make a backup for the IRIS server before upgrading platform or docker, and the procedure for rebuilding the IRIS in a new environment.

IRIS server backup procedure

When you have finished building for the IRIS server, you need to make a backup.

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One of the reasons why I love Cache and Iris is that not only you can do anything you can imagine, also you can do it in a lot of different ways!!.

Imagine that you have an integration running with IRIS connected by ODBC you probably only run SQL queries but you can also create stored procedures and inside write the code to do everything you can imagine.

I'm going to give you some examples but the limit is your imagination!!

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Make sure you have git installed.

I created a git folder inside the IRIS mgr directory. I right clicked the git folder and chose Git Bash Here from the context menu.

git clone

Clone my csp-log-tutorial GitHub repo if you like to try it out for yourself.

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Iryna Mykhailova · Mar 16 6m read
Kinds of properties in IRIS

InterSystems IRIS has quite a few different kinds properties. Let’s put them in order so that they make better sense.

First of all, I would divide them into categories:

  • Atomic or simple properties (all those %String, %Integer, %Data and other system or user datatypes)
  • References to stored objects
  • Built-in objects
  • Streams (both binary and character)
  • Collections (which are divided into arrays and lists)
  • Relationships (one-many and parent-children)

Some of these kinds of properties are quite straightforward. For example, atomic properties:

Property Name As %Name;
Property DoB As %Date
Property Age As %Integer

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Data analytics is a crucial aspect of business decision-making in today's fast-paced world. Organizations rely heavily on data analysis to make informed decisions and stay ahead of the competition. In this article, we will explore how data analytics can be performed using Pandas and Intersystems Embedded Python. We will discuss the basics of Pandas, the benefits of using Intersystems Embedded Python, and how they can be used together to perform efficient data analytics.

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