Amazon SageMaker vs. Azure HDInsight

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon SageMaker
Score 8.7 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
Azure HDInsight
Score 7.1 out of 10
N/A
HDInsight is an implementation of the Apache Hadoop technology stack on the Microsoft Azure cloud platform: It is based on the Hortonworks Hadoop distribution. Microsoft Azure HDInsight includes implementations of Apache Spark, HBase, Storm, Pig, Hive, Sqoop, Oozie, Ambari, etc. It also integrates with with business intelligence (BI) tools such as Power BI, Excel, SQL Server Analysis Services, and SQL Server Reporting Services.N/A
Pricing
Amazon SageMakerAzure HDInsight
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Amazon SageMakerAzure HDInsight
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Amazon SageMakerAzure HDInsight
Best Alternatives
Amazon SageMakerAzure HDInsight
Small Businesses
InterSystems IRIS
InterSystems IRIS
Score 7.8 out of 10

No answers on this topic

Medium-sized Companies
InterSystems IRIS
InterSystems IRIS
Score 7.8 out of 10
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Enterprises
Dataiku
Dataiku
Score 8.2 out of 10
IBM Analytics Engine
IBM Analytics Engine
Score 7.3 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon SageMakerAzure HDInsight
Likelihood to Recommend
9.0
(5 ratings)
4.0
(6 ratings)
Usability
-
(0 ratings)
8.9
(4 ratings)
Support Rating
-
(0 ratings)
1.0
(5 ratings)
User Testimonials
Amazon SageMakerAzure HDInsight
Likelihood to Recommend
Amazon AWS
It allows for one-click processes and for things to be auto checked before they are moved through the process but through the system. It also makes training easy. I am able to train users on the basic fundamentals of the tool and how it is used very easily as it is fully managed on its own which is incredible.
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Microsoft
Well suited: A tiny-mid sized company with no immediate plans of growing the volume of their data processing, that can afford long response times from support. Also it helps if you are not prone to put your hands on Linux and Spark configuration. In fact, it can make things go really faster if you also work with the bundle-in Jupyter. And, if you need to perform some diagnostics and / or administrative tasks, that's full of tools to find an understand the Root Cause. Ideal for non experts. Less appropriate: Big Data company, intense on demand cluster creation, mission critical, costs reduction, latest versions of libraries required, sophisticate customizations required.
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Pros
Amazon AWS
  • Machine Learning at scale by deploying huge amount of training data
  • Accelerated data processing for faster outputs and learnings
  • Kubernetes integration for containerized deployments
  • Creating API endpoints for use by technical users
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Microsoft
  • Data is presented without interfering others (IT or other dept).
  • Data is managed properly and is available for retrievable any time.
  • Legacy use of CD/DVD and Pendrive are not required.
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Cons
Amazon AWS
  • It's very good for the hardcore programmer, but a little bit complex for a data scientist or new hire who does not have a strong programming background.
  • Most of the popular library and ML frameworks are there, but we still have to depend on them for new releases.
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Microsoft
  • The only problem I have come across is when loading large volumes of data I sometimes get an error message, I assume this means something is corrupt from within. I would love a way for this to be resolved without having to start over.
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Usability
Amazon AWS
No answers on this topic
Microsoft
Azure HDInsight is usable on the top of Azure Data Lake and gives us the benefit of analyzing large scale data workload in Hadoop. Usability and support from Microsoft are outstanding.
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Support Rating
Amazon AWS
No answers on this topic
Microsoft
Inexpert, isolated teams... not good for support an excessively complex platform. Lots of weeks or months for a complex problem troubleshoot. Many time lost stuck on MindTree, before the case was finally escalated with Microsoft!
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Alternatives Considered
Amazon AWS
Amazon SageMaker took the heavy lifting out of building and creating models. It allowed for our organization to use our current system for integration and essentially added on a feature to help all levels of Data scientists and IT professionals in our department and company as a whole. The training was simple as well.
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Microsoft
At this time I have not used any other similar products... I am open to it but Azure HDInsight and its components really work well for our organization.
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Return on Investment
Amazon AWS
  • We have been able to deliver data products more rapidly because we spend less time building data pipelines and model servers.
  • We can prototype more rapidly because it is easy to configure notebooks to access AWS resources.
  • For our use-cases, serving models is less expensive with SageMaker than bespoke servers.
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Microsoft
  • ROI is of course there, as no legacy software for data presentation.
  • No manual intervention for data retrieval.
  • Data is available anywhere as requested.
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ScreenShots