Cloudera Data Platform vs. Keras

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Cloudera Data Platform
Score 6.5 out of 10
N/A
Cloudera Data Platform (CDP), launched September 2019, is designed to combine the best of Hortonworks and Cloudera technologies to deliver an enterprise data cloud. CDP includes the Cloudera Data Warehouse and machine learning services as well as a Data Hub service for building custom business applications.
$0.04
per CCU (hourly rate)
Keras
Score 7.7 out of 10
N/A
Keras is a Python deep learning libraryN/A
Pricing
Cloudera Data PlatformKeras
Editions & Modules
CDP Public Cloud - Data Hub
$0.04
per CCU (hourly rate)
CDP Public Cloud - Data Warehouse
$0.054
per CCU (hourly rate)
CDP Public Cloud - Data Engineering
$0.07
per CCU (hourly rate)
CDP Public Cloud - Operational Database
$0.08
per CCU (hourly rate)
CDP Public Cloud - Flow Management
$0.15
per CCU (hourly rate)
CDP Public Cloud - Machine Learning
$0.17
per CCU (hourly rate)
CDP Private Cloud - Plus Edition
$400
CCU (annual subscription)
CDP Private Cloud - Base Edition
$10,000.00
node + variable (annual subscription)
No answers on this topic
Offerings
Pricing Offerings
Cloudera Data PlatformKeras
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
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Cloudera Data PlatformKeras
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Medium-sized Companies
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Score 9.0 out of 10
Posit
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Score 9.1 out of 10
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Oracle Exadata
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Score 8.2 out of 10
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Score 7.8 out of 10
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User Ratings
Cloudera Data PlatformKeras
Likelihood to Recommend
7.0
(1 ratings)
8.1
(6 ratings)
Usability
-
(0 ratings)
7.7
(2 ratings)
Support Rating
8.0
(1 ratings)
8.2
(2 ratings)
User Testimonials
Cloudera Data PlatformKeras
Likelihood to Recommend
Cloudera
I have seen that Cloudera Data Platform is well suited for large batch processes. It works really well for our indication analyses that are performed by the actuaries. I feel that rapid streaming operations may be a situation where additional technology would be needed to provide for a robust solution.
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Open Source
Keras is quite perfect, if the aim is to build the standard Deep Learning model, and materialize it to serve the real business use case, while it is not suitable if the purpose is for research and a lot of non-standard try out and customization are required, in that case either directly goes to low level TensorFlow API or Pytorch
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Pros
Cloudera
  • Scales
  • Highly available
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Open Source
  • One of the reason to use Keras is that it is easy to use. Implementing neural network is very easy in this, with just one line of code we can add one layer in the neural network with all it's configurations.
  • It provides lot of inbuilt thing like cov2d, conv2D, maxPooling layers. So it makes fast development as you don't need to write everything on your own. It comes with lot of data processing libraries in it like one hot encoder which also makes your development easy and fast.
  • It also provides functionality to develop models on mobile device.
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Cons
Cloudera
  • Constantly changing costs
  • Log visibility
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Open Source
  • As it is a kind of wrapper library it won't allow you to modify everything of its backend
  • Unlike other deep learning libraries, it lacks a pre-defined trained model to use
  • Errors thrown are not always very useful for debugging. Sometimes it is difficult to know the root cause just with the logs
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Usability
Cloudera
No answers on this topic
Open Source
I am giving this rating depending on my experience so far with Keras, I didn't face any issue far. I would like to recommend it to the new developers.
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Support Rating
Cloudera
We have utilized Cloudera support quite frequently and are very satisfied with the capability and responsiveness of that team. Often, the new features delivered with the platform give us an opportunity to mature the way we're doing things, and the support team have been valuable in developing those new patterns.
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Open Source
Keras have really good support along with the strong community over the internet. So in case you stuck, It won't so hard to get out from it.
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Alternatives Considered
Cloudera
IBM's offering of the Cloud Pak for Data has been a moving target and difficult to compare to Cloudera Data Platform. We have implemented our solution on Amazon Web Services, which appears to be supported by IBM at this point, but the migration would be very expensive for us to endeavor.
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Open Source
Keras is good to develop deep learning models. As compared to TensorFlow, it's easy to write code in Keras. You have more power with TensorFlow but also have a high error rate because you have to configure everything by your own. And as compared to MATLAB, I will always prefer Keras as it is easy and powerful as well.
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Return on Investment
Cloudera
  • Reduced operational costs
  • Speed to market
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Open Source
  • Easy and faster way to develop neural network.
  • It would be much better if it is available in Java.
  • It doesn't allow you to modify the internal things.
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