We performed a comparison between Dremio and Microsoft Azure Machine Learning Studio based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Dremio gives you the ability to create services which do not require additional resources and sterilization."
"The most valuable feature of Dremio is it can sit on top of any other data storage, such as Amazon S3, Azure Data Factory, SGFS, or Hive. The memory competition is good. If you are running any kind of materialized view, you'd be running in memory."
"We primarily use Dremio to create a data framework and a data queue."
"Dremio allows querying the files I have on my block storage or object storage."
"Dremio enables you to manage changes more effectively than any other data warehouse platform. There are two things that come into play. One is data lineage. If you are looking at data in Dremio, you may want to know the source and what happened to it along the way or how it may have been transformed in the data pipeline to get to the point where you're consuming it."
"Everyone uses Dremio in my company; some use it only for the analytics function."
"The most valuable feature of this solution is the ability to use all of the cognitive services, prebuilt from Azure."
"The initial setup is very simple and straightforward."
"ML Studio is very easy to maintain."
"Azure Machine Learning Studio's most valuable features are the package from Azure AutoML. It is quite powerful compared to the building of ML in Databricks or other AutoMLs from other companies, such as Google and Amazon."
"The visualizations are great. It makes it very easy to understand which model is working and why."
"The solution is very easy to use, so far as our data scientists are concerned."
"It's easy to use."
"Their web interface is good."
"Dremio doesn't support the Delta connector. Dremio writes the IT support for Delta, but the support isn't great. There is definitely room for improvement."
"It shows errors sometimes."
"They have an automated tool for building SQL queries, so you don't need to know SQL. That interface works, but it could be more efficient in terms of the SQL generated from those things. It's going through some growing pains. There is so much value in tools like these for people with no SQL experience. Over time, Dermio will make these capabilities more accessible to users who aren't database people."
"We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"Dremio takes a long time to execute large queries or the executing of correlated queries or nested queries. Additionally, the solution could improve if we could read data from the streaming pipelines or if it allowed us to create the ETL pipeline directly on top of it, similar to Snowflake."
"The AutoML feature is very basic and they should improve it by using a more robust algorithm."
"In the future, I would like to see more AI consultation like image and video classification, and improvement in the presentation of data."
"I would like to see modules to handle Deep Learning frameworks."
"When you use different Microsoft tools, there are different pricing metrics. It doesn't make sense. The pricing metrics are quire difficult to understand and should be either clarified or simplified. It would help us sell the solution to customers."
"The product must improve its documentation."
"The data cleaning functionality is something that could be better and needs to be improved."
"As for the areas for improvement in Microsoft Azure Machine Learning Studio, I've provided feedback to Microsoft. My company is a Gold Partner of Microsoft, so I provided my feedback in another forum. Right now, it is the number of algorithms available in the designer that has to be improved, though I'm sure Microsoft does it regularly. When you take a use case approach, Microsoft has done that in a lot of places, but not on the Microsoft Azure Machine Learning Studio designer. When I say use case basis, I meant recommending a product or recommending similar products, so if Microsoft can list out use cases and give me a template, it will save me a lot of time and a lot of work because I don't have to scratch my head on which algorithm is better, and I can go with what's recommended by Microsoft. I'm sure that isn't a big task for the Microsoft team who must have seen thousands of use cases already, so out of that experience if the team can come up with a standard template, I'm sure it'll help a lot of organizations cut down on the development time, as well as going with the best industry-standard algorithms rather than experimenting with mine. What I'd like to see in the next version of Microsoft Azure Machine Learning Studio, apart from the use case template, is the improvement of the availability of libraries. Microsoft should also upgrade the Python versions because the old version of Python is still supported and it takes time for Microsoft to upgrade the support for Python. The pace of upgrading Python versions of Microsoft Azure Machine Learning Studio and making those libraries available should be sped up or increased."
"There should be data access security, a role level security. Right now, they don't offer this."
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Dremio is ranked 9th in Data Science Platforms with 6 reviews while Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 51 reviews. Dremio is rated 8.6, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of Dremio writes "It enables you to manage changes more effectively than any other platform". On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Good support for Azure services in pipelines, but deploying outside of Azure is difficult". Dremio is most compared with Databricks, Snowflake, Starburst Enterprise, Amazon Redshift and Microsoft Azure Synapse Analytics, whereas Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI, TensorFlow and Google Cloud AI Platform. See our Dremio vs. Microsoft Azure Machine Learning Studio report.
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