Before we start talking about databases and different data models that exist, first we'd better talk about what a database is and how to use it.

A database is an organized collection of data stored and accessed electronically. It is used to store and retrieve structured, semi-structured, or raw data which is often related to a theme or activity.

At the heart of every database lies at least one model used to describe its data. And depending on the model it is based on, a database may have slightly different characteristics and store different types of data.

To write, retrieve, modify, sort, transform or print the information from the database, a software called Database Management System (DBMS) is used.

The size, capacity, and performance of databases and their respective DBMS have increased by several orders of magnitude. It has been made possible by technological advances in various areas, such as processors, computer memory, computer storage, and computer networks. In general, the development of database technology can be divided into four generations based on the data models or structure: navigational, relational, object and post-relational.

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Article
Rob Tweed · Dec 20, 2021 1m read
Holiday Reading: What Lies Beneath!

For those of you who might be new to IRIS, and even those who have used Cache or IRIS for some time but want to explore beyond its usually-assumed boundaries and practices, you might want to dive into this detailed exploration of the database engine that is at its heart, and discover just what you can really do with it, going way beyond what InterSystems have done with it for you.

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Image search like Google's is a nice feature that wonder me - as almost anything related to image processing.

A few months ago, InterSystems released a preview for Python Embedded. As Python has a lot of libs for deal with image processing, I decided to start my own attemptive to play with a sort of image search - a much more modest version in deed :-)

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Making a blog using Python + IRIS Globals

Since I started to use internet (late 90's), I always had a CMS (content management system) present to make easier post
any information in a blog, social media or even an enterprise page. And later years putting all my code into github I
used to document it on a markdown file. Observing how easy could be persisting data into Intersystems IRIS with the
Native API I decided to make this application and force myself to forget a little of SQL and stay open to key-value database
model.

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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:

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QEWD is assumed by most people to only integrate with IRIS (or Cache) via a connection through IRIS's high-performance C interface. This requires QEWD (and its Node.js environment) to be installed and configured on the same machine as IRIS.

I'm frequently asked if QEWD can run on a separate server (or servers), and access IRIS (or Cache) over a network connection. The answer is yes it can, but the information on how to set it up in this way has been admittedly a bit tricky to discover.

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