If you need write your organization Data Architecture and map to the InterSystems IRIS, consider following Data Architecture Diagram and references to the intersystems iris documentation, see:

A concurrent session in IRIS:
SQL, Objects, REST, and GraphQL

Kazimir Malevich, "Athletes" (1932)

"But of course you don't understand! How can a person who has always traveled in a horse-drawn carriage understand the feelings and impressions of the express traveler or the pilot in the air?"

Kazimir Malevich (1916)

Introduction

We’ve already addressed the topic of why object/type representation is superior to SQL for implementing subject area models. And those conclusions and facts are as true now as they have ever been. So why should we take a step back and discuss technologies that drag abstractions back to the global level, where they had been in the pre-object and pre-type era? Why should we encourage the use of spaghetti code, which results in bugs that are hard to track down, and which relies only on virtuoso developer skills?

There are several arguments in favor of transmitting data via SQL/REST/GraphQL-based APIs as opposed to representing them as types/objects:

Beginning - see Part 1.

3. Variants of structures when using globals

A structure, such as an ordered tree, has various special cases. Let's take a look at those that have practical value for working with globals.

3.1 Special case 1. One node without branches

Process-private Globals can be used as a data global in storage definition. That way, each process can have its own objects for the class with ppg storage. For example lets define a pool, which can:

• add elements to a pool (ignoring duplicates)
• check if an element exists in the pool

Here's the class:

Headache-free stored objects: a simple example of working with InterSystems Caché objects in ObjectScript and Python

Neuschwanstein Castle

Tabular data storages based on what is formally known as the relational data model will be celebrating their 50th anniversary in June 2020. Here is an official document – that very famous article. Many thanks for it to Doctor Edgar Frank Codd. By the way, the relational data model is on the list of the most important global innovations of the past 100 years published by Forbes.

On the other hand, oddly enough, Codd viewed relational databases and SQL as a distorted implementation of his theory. For general guidance, he created 12 rules that any relational database management system must comply with (there are actually 13 rules). Honestly speaking, there is zero DBMS's on the market that observes at least Rule 0. Therefore, no one can call their DBMS 100% relational :) If you know any exceptions, please let me know.

Let's consider you would like to efficiently store your historical data in a similar structure than the one used for your current data, but without sharing the same physical storage (ie : not in the same global). What is the most efficient way to do it ?

Below a simple class of your current data :

In this article I'd like to share with you a phenomena that is best you avoid - something you should be aware of when designing your data model (or building your Business Processes) in Caché or in Ensemble (or older HealthShare Health Connect Ensemble-based versions).

How Tax Service, OpenStreetMap, and InterSystems IRIS
could help developers get clean addresses

Pieter Brueghel the Younger, Paying the Tax (The Tax Collector), 1640

In my previous article, we just skimmed the surface of objects. Let's continue our reconnaissance. Today's topic is a tough one. It's not quite BIG DATA, but it's still the data not easy to work with: we're talking about fairly large amounts of data. It won't all fit into RAM at once, and some of it won't even fit on the drive (not due to lack of space, but because there's a lot of junk). The name of our subject is FIAS DB: the Federal Information Address System database - the databases of addresses in Russia. The archive is 5.5 GB. And it's a compressed XML file. After extraction, it will be a full 53 GB (set aside 110 GB for extraction). And when you start to parse and convert it, that 110 GB won't be enough. There won't be enough RAM either.

When do implicit assumptions in code and arithmetic operators pose a real danger, and how can this danger be overcome?

Constantinople in the 5th century AD

(It was possible for people to build grandiose buildings and vehicles without the use of computers and robots 1,600 years ago.)

I have an application with maps that render and edit geographic data in a some layers using KML - geo data represented into XML file with layers, polygnons, points and metadata associated with it. Some maps are in GeoJSON too.

Is it DocDB the better option?

Just wondering an Insight in the difference between these two indexes

IdKey / PrimaryKey
=================

Property Identifier As %Integer

Index Index1 on Identifier [Idkey]

Index Index2 on Identifier [PrimaryKey]

What's the difference?

1. If I don't have Index1 and only have Index2, then cache does still make its own id.
So how and why do I ever use the PrimaryKey. In Joins ??

For the benefit of those who want to use the Document Database (DocDB) capabilities within InterSystems IRIS, and specifically the REST API it provides, I put together a Postman Collection that provides samples for several basic calls.

For example:

Hi Community,

New video, recorded by @Stefan Wittmann, is already on InterSystems Developers YouTube:

🗣 Dynamic Data with JSON

https://www.youtube.com/embed/b2GYVDP6VvM
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