This is the third part of the series of articles on migrating from the main databases on the market to InterSystems IRIS. In this part, the procedures for migrating from DB2 will be detailed.As described in previous articles, there are currently a few options to do the migration. However, the two most popular options include the usage of DBeaver (https://openexchange.intersystems.com/package/DBeaver) or SQLGateway.

This article is a follow-up to the previous one on how to migrate from popular databases (like PostgreSQL and MySQL) to IRIS.
We will use the same procedures utilized to migrate from PostgreSQL. However, you will see that it is even easier since the data types in MySQL are very similar to IRIS. That is why we will not need to create transformation rules in the columns.

Get the sample data to the migration process

In GitHub it is possible to download a docker-compose project to build and run 2 databases:

If you need create a upload REST API with IRIS is very simple. Do these procedures:

From Postman client you send a file

P.S.: It is a multipart form with a file type using "file" in the name. The request type is form/multipart. See the http request:

@Robert Cemper is the most active and widely read member of the community (Best Seller!). So nothing better than learning InterSystems technologies from over 100 articles by him. I curated the articles, selecting the best ones by subject:

The JSON is a data document free of types and validation rules. However, in some scenarios it is important that the JSON document has type and business rules validation, especially in interoperability scenarios. This article demonstrates how you can leverage a market-defined JSONSchema technology that is open for everyone to use and do advanced validations.

Hi Community,

In a hard work of data curation and data quality, the Health Dataset application deploy to you the above datasets.

These datasets can be used in your ML applications/models, AutoML and analytics projects. See more details here:

The InterSystems IRIS IntegratedML feature is used to get predictions and probabilities using the AutoML technique. The AutoML is a Machine Learning technology used to select the better Machine Learning algorithm/model to predict status, numbers and general results based in the past data (data used to train the AutoML model). You don't need a Data Scientist, because the AutoML it will test the most common Machine Learning algorithms and select the better algorithm to you, based in the data features analysed. See more here, in this article.

The InterSystems IRIS has a great audit system. It is responsible for auditing system events, but you can use it to audit your applications (great feature).

The audit system is based into event concept. The events can occur with IRIS or in an application. So, we have two type of events to the audit system:

1. System events: events occured into the InterSystems IRIS components (database, interoperability, analytics and core);