Azure Machine Learning vs. InterSystems IRIS

For [a] data scientist require[d] to build a machine learning model, so he/she didn't worry about infrastructure to maintain it.

All kind of feature[s] such as train, build, deploy and monitor the machine learning model available in a single suite.

If someone has [their] own environment for ML studio, so there [it would] not [be] useful for them.

Intersystems IRIS is a really great tool for Interoperability. It has so many capabilities out of the box and then such a great developer community on top of that, that there are really no limits to what you can do in terms of data manipulation and translation. Personally I find it to be a great tool if you are looking for Interoperability software.

Incentivized

• User friendliness: This is by far the most user friendly tool I've seen in analytics. You don't need to know how to code at all! Just create a few blocks, connect a few lines and you are capable of running a boosted decision tree with a very high R squared!
• Speed: Azure ML is a cloud based tool, so processing is not made with your computer, making the reliability and speed top notch!
• Cost: If you don't know how to code, this is by far the cheapest machine learning tool out there. I believe it costs less than $15/month. If you know how to code, then R is free.
• Connectivity: It is super easy to embed R or Python codes on Azure ML. So if you want to do more advanced stuff, or use a model that is not yet available on Azure ML, you can simply paste the code on R or Python there!
• Microsoft environment: Many many companies rely on the Microsoft suite. And Azure ML connects perfectly with Excel, CSV and Access files.

Incentivized

• Connecting with mutliple vendor platforms and systems allowing us to consume and provide data as needed.
• Allowed us to implement our own RESTful api engine to server data to our internal applications.
• Setting up their recommendations for high availability allow us to perform server maintenance with minimal down time to our users.

• It would be great to have text tips that could ease new users to the platform, especially if an error shows up
• Scenario-based documentation
• Pre-processing of modules that had been previously run. Sometimes they need to be re-run for no apparent reason

Incentivized

• Enhanced documentation, more comprehensive and user-friendly documentation, including detailed tutorials and examples
• Improving compatibility and integrations with others programming languages
• Introducing tools and techniques to optimize the performance of ObjectScript applications, such as profiling tools, performance monitoring utilities, and code optimization guidelines
• A better compatibility with Python libraries

Easy and fastest way to develop, test, deploy and monitor the machine learning model.

- Easy to load the data set

-Drag and drop the process of the Machine learning life cycle.

It could do with some additional support for languages and frameworks that are widely used by developers today. For example, it could also integrate the use of AI Coding agents or AI tools to speed up application development processes. It could also include better SSH support to allow developers to remotely edit and maintain applications.

Support is nonexistent. It's very frustrating to try and find someone to actually talk to. The robot chatbots are just not well trained.

Incentivized

The support team is the best in the world. All you need they can help you. The documentation is very good, but the support team can help you in less than 24h (some hours if it's very urgent).

Also, there is a great developers team in a good community that can help you in several languages (English, Spanish, Japanese, Portuguese, etc.).

Not sure

Will done based on a proper planning, so this will makes execution more easier and better.

It is easier to learn, it has a very cost effective license for use, it has native build and created for Azure cloud services, and that makes it perfect when compared against the alternatives. As a Microsoft tool, it has been built to contain many visual features and improved usability even for non-specialist users.

Incentivized

We are using InterSystems IRIS [especially] for database operations as the query performance is really good for [a large] amount of customer data. You can easily integrate for any application like web, desktop, and many more. It also provides BI functionality which is also very easy to implement using InterSystems IRIS[.]

• Productivity: Instead of coding and recoding, Azure ML helped my organization to get to meaningful results faster;
• Cost: Azure ML can save hundreds (or even thousands) of dollars for an organization, since the license costs around $15/month per seat.
• Focus on insights and not on statistics: Since running a model is so easy, analysts can focus more on recommendations and insights, rather than statistical details

Incentivized

• Very Fast and scalable software to deal with big data flow, safe and robust.
• The studio IDE is quite old fashion and lacks a few facilities
• amazing for complex data consumption, its milyi-model capability wich allows multiple different models for a single set of codes.