#SQL

Hi, Community!

This article is an overview of SQLAlchemy, so let's begin!

SQLAlchemy is the Python SQL toolkit that serves as a bridge between your Python code and the relational database system of your choice. Created by Michael Bayer, it is currently available as an open-source library under the MIT License. SQLAlchemy supports a wide range of database systems, including PostgreSQL, MySQL, SQLite, Oracle, and Microsoft SQL Server, making it versatile and adaptable to different project requirements.

The SQLAlchemy SQL Toolkit and Object Relational Mapper from a comprehensive set of tools for working with databases and Python. It has several distinct areas of functionality which you can use individually or in various combinations. The major components are illustrated below, with component dependencies organized into layers:

The Art of Mapping Globals to Classes (4 of 3)

The forth in the trilogy, anyone a Hitchhikers Guide to the Galaxy fan?

If you are looking to breathe new life into an old MUMPS application follow these steps to map your globals to classes and expose all that beautiful data to Objects and SQL.

If the above does not sound familiar to you please start at the beginning with the following:

The Art of Mapping Globals to Classes (1 of 3)

I recently met an ages old issue related to code maintenance:

• You have access to your IRIS server just over ODBC/JDBC
• no VSCode access, no Studio access
• no (Web-)Terminal access

But you need to take a look on Classes or Routines or Globals !!
Anyhow SQL is your friend.

In this article we are going to show the results of the comparision between IRIS and Postgress when handling Astronomy data.

Introduction

Since the earliest days of human civilization we have been fascinated by the sky at night. There are so many stars! Everybody has dreamed about them and fantasized about life in other planets.

Nowadays so much noise around LLM, AI, and so on. Vector databases are kind of a part of it, and already many different realizations for the support in the world outside of IRIS.

Why Vector?

• Similarity Search: Vectors allow for efficient similarity search, such as finding the most similar items or documents in a dataset. Traditional relational databases are designed for exact match searches, which are not suitable for tasks like image or text similarity search.
• Flexibility: Vector representations are versatile and can be derived from various data types, such as text (via embeddings like Word2Vec, BERT), images (via deep learning models), and more.
• Cross-Modal Searches: Vectors enable searching across different data modalities. For instance, given a vector representation of an image, one can search for similar images or related texts in a multimodal database.

And many other reasons.

So, for this pyhon contest, I decided to try to implement this support. And unfortunately I did not manage to finish it in time, below I'll explain why.

Order is a necessity for everyone, but not everyone understands it in the same way
(Fausto Cercignani)

Disclaimer: This article uses Russian language and Cyrillic alphabet as examples, but is relevant for anyone who uses Caché in a non-English locale.
Please note that this article refers mostly to NLS collations, which are different than SQL collations. SQL collations (such as SQLUPPER, SQLSTRING, EXACT which means no collation, TRUNCATE, etc.) are actual functions that are explicitly applied to some values, and whose results are sometimes explicitly stored in the global subscripts. When stored in subscripts, these values would naturally follow the NLS collation in effect (“SQL and NLS Collations”).

GmOwl is a solution that offers an organized and engaging learning platform. It was developed to cater to the increasing need, for learning tools providing a versatile quiz environment that meets users requirements.

The main objective of GmOwl is to deliver an user experience for individuals participating in quizzes while giving administrators comprehensive control, over content and user engagement.

GmOwl uses Java EE with MVC template, and the InterSystems IRIS database is used to store data. The InterSystems JDBC Driver is used to connect to the database.

End users sure love Excel tables. So, how can you deliver the second to the first? Read this post to find out.

In the good old days (tm) determining the size of the data, streams, and indices for a class/table was easy - you just ran %GSIZE and check D, S, and I globals respectively.

However, nowadays sharding, optimized global names, and indices in separate globals produce %GSIZE output looking like this:

In the vast and varied SQL database market, InterSystems IRIS stands out as a platform that goes way beyond just SQL, offering a seamless multimodel experience and supporting a rich set of development paradigms. Especially the advanced Object-Relational engine has helped organizations use the best-fit development approach for each facet of their data-intensive workloads, for example ingesting data through Objects and simultaneously querying it through SQL. Persistent Classes correspond to SQL tables, their properties to table columns and business logic is easily accessed using User-Defined Functions or Stored Procedures. In this article, we'll zoom in on a little bit of the magic just below the surface, and discuss how it may affect your development and deployment practices. This is an area of the product where we have plans to evolve and improve, so please don't hesitate to share your views and experiences using the comments section below.

The last days I've work with the great new feature: LOAD DATA With this post I would like to share my first experiences with you. The following points do not contain any order or other evaluation. These are only things that I noticed when using the LOAD DATA command. It should also be noted that these points are based on the IRIS Version 2021.2.0.617 which is a preview release. So it may be that my observations do not apply to newer IRIS versions.

Hi Community,

In this article, we will explore the concepts of Dynamic SQL and Embedded SQL within the context of InterSystems IRIS, provide practical examples, and examine their differences to help you understand how to leverage them in your applications.

InterSystems SQL provides a full set of standard relational features, including the ability to define table schema, execute queries, and define and execute stored procedures. You can execute InterSystems SQL interactively from the Management Portal or programmatically using a SQL shell interface. Embedded SQL enables you to embed SQL statements in your ObjectScript code, while Dynamic SQL enables you to execute dynamic SQL statements from ObjectScript at runtime. While static SQL queries offer predictable performance, dynamic and embedded SQL offer flexibility and integration, respectively.

Introduction

This is a simple tutorial on the quickest way I found to create a sample database for any purposes such as testing, making samples for tutorials, etc.

Creating a namespace

1. Open the terminal
2. Write the command "D $SYSTEM.SQL.Shell()"
3. Write "CREATE DATABASE " and the name you want for your namespace.

Now you have a new namespace in a faster way than creating it from the Management Portal - which of course offers way more configuration options.