Compare Google Cloud Datalab vs. RapidMiner

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Google Cloud Datalab Logo
3,034 views|2,669 comparisons
RapidMiner Logo
8,868 views|6,948 comparisons
Most Helpful Review
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Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
"All of the features of this product are quite good."

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"The documentation for this solution is very good, where each operator is explained with how to use it.""The most valuable features are the Binary classification and Auto Model.""The most valuable feature is what the product sets out to do, which is extracting information and data.""The most valuable feature of RapidMiner is that it can read a large number of file formats including CSV, Excel, and in particular, SPSS.""Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations.""The best part of RapidMiner is efficiency.""The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model.""RapidMiner is very easy to use."

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Cons
"The interface should be more user-friendly."

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"The price of this solution should be improved.""RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models.""A great product but confusing in some way with regard to the user interface and integration with other tools.""It would be helpful to have some tutorials on communicating with Python.""The visual interface could use something like the-drag-and-drop features which other products already support. Some additional features can make RapidMiner a better tool and maybe more competitive.""I think that they should make deep learning models easier.""The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator.""I would like to see all users have access to all of the deep learning models, and that they can be used easily."

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Pricing and Cost Advice
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"I used an educational license for this solution, which is available free of charge.""Although we don't pay licensing fees because it is being used within the university, my understanding is that the cost is between $5,000 and $10,000 USD per year.""The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license."

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Top Answer: The data science, collaboration, and IDN are very, very strong.
Top Answer: The solution is considered expensive, at least in the Latin American market. They do try their best to give discounts whenever it's possible. However, the overall price is something to be cautious… more »
Top Answer: In the Mexican or Latin American market, it's kind of pricey. The pricing can be a bit high. Some of the data science platforms offer much more flexibility. Of course, there's not the same software… more »
Ranking
19th
Views
3,034
Comparisons
2,669
Reviews
1
Average Words per Review
303
Rating
8.0
7th
Views
8,868
Comparisons
6,948
Reviews
8
Average Words per Review
660
Rating
8.5
Popular Comparisons
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Overview

Cloud Datalab is a powerful interactive tool created to explore, analyze, transform and visualize data and build machine learning models on Google Cloud Platform. It runs on Google Compute Engine and connects to multiple cloud services easily so you can focus on your data science tasks.

RapidMiner's unified data science platform accelerates the building of complete analytical workflows - from data prep to machine learning to model validation to deployment - in a single environment, improving efficiency and shortening the time to value for data science projects.

Offer
Learn more about Google Cloud Datalab
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Sample Customers
Information Not Available
PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen
Top Industries
VISITORS READING REVIEWS
Comms Service Provider25%
Computer Software Company22%
Financial Services Firm11%
Retailer8%
REVIEWERS
University43%
Energy/Utilities Company14%
Educational Organization14%
Engineering Company14%
VISITORS READING REVIEWS
Computer Software Company22%
Comms Service Provider21%
University9%
Government7%
Company Size
No Data Available
REVIEWERS
Small Business62%
Midsize Enterprise8%
Large Enterprise31%
VISITORS READING REVIEWS
Small Business31%
Midsize Enterprise3%
Large Enterprise66%
Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: June 2021.
511,607 professionals have used our research since 2012.

Google Cloud Datalab is ranked 19th in Data Science Platforms with 1 review while RapidMiner is ranked 7th in Data Science Platforms with 9 reviews. Google Cloud Datalab is rated 8.0, while RapidMiner is rated 8.4. The top reviewer of Google Cloud Datalab writes "Stable, feature-rich, and easy to set up". On the other hand, the top reviewer of RapidMiner writes "Offers good tutorials that make it easy to learn and use, with a powerful feature to compare machine learning algorithms". Google Cloud Datalab is most compared with Databricks, IBM Watson Studio, Microsoft Azure Machine Learning Studio, Cloudera Data Science Workbench and MathWorks Matlab, whereas RapidMiner is most compared with KNIME, Alteryx, Dataiku Data Science Studio, Tableau and Microsoft Azure Machine Learning Studio.

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