Amazon SageMaker vs. InterSystems IRIS

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon SageMaker
Score 8.2 out of 10
N/A
Amazon SageMaker enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.N/A
InterSystems IRIS
Score 7.7 out of 10
N/A
InterSystems IRIS is a complete cloud-first data platform that includes a multi-model transactional data management engine, an application development platform, and interoperability engine, and an open analytics platform. It is is the next generation of InterSystems' data management software. It includes…N/A
Pricing
Amazon SageMakerInterSystems IRIS
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Amazon SageMakerInterSystems IRIS
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeOptional
Additional Details
More Pricing Information
Community Pulse
Amazon SageMakerInterSystems IRIS
Best Alternatives
Amazon SageMakerInterSystems IRIS
Small Businesses
InterSystems IRIS
InterSystems IRIS
Score 7.7 out of 10
Google Cloud SQL
Google Cloud SQL
Score 8.9 out of 10
Medium-sized Companies
InterSystems IRIS
InterSystems IRIS
Score 7.7 out of 10
Google Cloud SQL
Google Cloud SQL
Score 8.9 out of 10
Enterprises
InterSystems IRIS
InterSystems IRIS
Score 7.7 out of 10
SAP IQ
SAP IQ
Score 10.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon SageMakerInterSystems IRIS
Likelihood to Recommend
9.0
(0 ratings)
7.4
(0 ratings)
Likelihood to Renew
-
(0 ratings)
8.2
(0 ratings)
Usability
-
(0 ratings)
8.2
(0 ratings)
Support Rating
-
(0 ratings)
7.4
(0 ratings)
Implementation Rating
-
(0 ratings)
8.2
(0 ratings)
User Testimonials
Amazon SageMakerInterSystems IRIS
Likelihood to Recommend
Amazon Sagemaker suits well in areas of data science and Machine learnings where medium to high-volume data is to be used for analysis. For a lean and platform agnostic deployment, it provides kubernetes integration to containerize the solution and deploy on any platform. It is one of the best solution for technical users for training Machine Learning models.
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It is best suited in the scenario where a single interface is required for providing [a complete end-to-end] solution to the customers. You don't need [a] separate platform to write code or [perform] database operations. All you need is InterSystems IRIS software and you are done. You can also use analytics functionality which is one of the greatest [features] which many customers need for their solution[.]
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Pros
  • SageMaker is useful as a managed Jupyter notebook server. Using the notebook instances' IAM roles to grant access to private S3 buckets and other AWS resources is great. Using SageMaker's lifecycle scripts and AWS Secrets Manager to inject connection strings and other secrets is great.
  • SageMaker is good at serving models. The interface it provides is often clunky, but a managed, auto-scaling model server is powerful.
  • SageMaker is opinionated about versioning machine learning models and useful if you agree with its opinions.
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  • 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.
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Cons
  • Searching and descriptions can be easier to read and interpret.
  • Training modules and customer service training representative could make on boarding employees easier.
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  • 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
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Usability
No answers on this topic
The interface is very intuitive, the documentation is very good so it is not complicated to operate.
The security is complex, but you can create a special role to access and the user ONLY can operate with the part that it allows.
Also, you can examine the data very quick with the SQL Browser integrated.
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Support Rating
No answers on this topic
The InterSystems WRC has always been helpful and responsive. The folks I have spoken with are always understanding of our needs and questions and regardless of if the question is simple or complex we are always met with the same professionalism and helpfulness every time. I have no hesitations contacting InterSystems for help!
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Implementation Rating
No answers on this topic
Will done based on a proper planning, so this will makes execution more easier and better.
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Alternatives Considered
We have not invested in another machine learning software at this time and so far this has proved very successful with our machine learning teams. As mentioned, I am training these individuals simply on the fundamentals of the software and using it/customizing it for their needs. It has been very easy to do this and has gotten great reviews across the organization so far.
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Tibco was not originally planned to be used for HL7 Integrations and as such we had to create some very complicated processes in order for the messages to parse and validate appropriately. It was simply not built for this type of interoperability. Comparatively, InterSystems IRIS for Health (HealthConnect) has out of the box HL7 features that would parse messages, offer a variety of validation options, simplified data lookups and transformation and reduced the amount of time it took to develop connections with out vendor systems. InterSystems IRIS also allows one to push just single files into production at a time so there is less of a chance of us pushing something that should not be in production yet as our previous system was set up to with TIBCO deployments
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Return on Investment
  • Using SageMaker, we can truly implement 'fail early, learn fast,' using an on-demand server for training.
  • It also saves your money from investing in a physical server for very rare use.
  • However, the pricing is high, but it will cost you only for what you use.
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  • 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.
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ScreenShots