Azure Databricks vs. Keras

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure Databricks
Score 8.7 out of 10
N/A
Azure Databricks is a service available on Microsoft's Azure platform and suite of products. It provides the latest versions of Apache Spark so users can integrate with open source libraries, or spin up clusters and build in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. The solution includes autoscaling and auto-termination to improve…N/A
Keras
Score 7.0 out of 10
N/A
Keras is a Python deep learning libraryN/A
Pricing
Azure DatabricksKeras
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure DatabricksKeras
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
Azure DatabricksKeras
Considered Both Products
Azure Databricks
Chose Azure Databricks
Against all the tools I have used, Azure Databricks is by far the most superior of them all! Why, you ask? The UI is modern, the features are never ending and they keep adding new features. And to quote Apple, "It just works!"
Far ahead of the competition, the delta lakehouse …
Keras
Chose Keras
As Keras is the high level API, so using Keras, we don't have to be bothered by the low level TensorFlow complexity, and we can reduce a lot coding and testing efforts.
Chose Keras
For beginners, I always recommend starting with Keras, because it's really easy to use and learn at first. There is not much pre-requisite for this to start with.
Chose Keras
Keras is much easier to learn as compared to TensorFlow. It also has a lot of built-in functionality that makes it much better than the alternatives.
Chose Keras
Keras is a good point where you can learn lots of things and also have hands-on experience. There is not much comparison of Keras with Tensorlow, as Keras is a wrapper library which supports TensorFlow and Theano as backends for computation. But once you have enough knowledge …
Chose Keras
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 …
Chose Keras
TensorFlow and Caffe are bit hard to learn but they give you power to implement everything by you own. But most of the time it is not required to implement our own algorithm, we can solve the problem with just using the already provided algorithms. As compared to TensorFlow and …
Features
Azure DatabricksKeras
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Azure Databricks
8.1
Ratings
3% below category average
Keras
-
Ratings
Connect to Multiple Data Sources6.20 Ratings00 Ratings
Extend Existing Data Sources9.00 Ratings00 Ratings
Automatic Data Format Detection9.00 Ratings00 Ratings
MDM Integration8.00 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Azure Databricks
6.4
Ratings
27% below category average
Keras
-
Ratings
Visualization5.90 Ratings00 Ratings
Interactive Data Analysis6.90 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Azure Databricks
8.0
Ratings
2% below category average
Keras
-
Ratings
Interactive Data Cleaning and Enrichment7.00 Ratings00 Ratings
Data Transformations9.00 Ratings00 Ratings
Data Encryption9.00 Ratings00 Ratings
Built-in Processors7.10 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Azure Databricks
8.3
Ratings
1% below category average
Keras
-
Ratings
Multiple Model Development Languages and Tools8.10 Ratings00 Ratings
Automated Machine Learning9.00 Ratings00 Ratings
Single platform for multiple model development8.00 Ratings00 Ratings
Self-Service Model Delivery8.00 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Azure Databricks
8.5
Ratings
0% below category average
Keras
-
Ratings
Flexible Model Publishing Options8.00 Ratings00 Ratings
Security, Governance, and Cost Controls9.00 Ratings00 Ratings
Best Alternatives
Azure DatabricksKeras
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 9.4 out of 10
InterSystems IRIS
InterSystems IRIS
Score 7.7 out of 10
Medium-sized Companies
Posit
Posit
Score 10.0 out of 10
Posit
Posit
Score 10.0 out of 10
Enterprises
Posit
Posit
Score 10.0 out of 10
Posit
Posit
Score 10.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Azure DatabricksKeras
Likelihood to Recommend
9.8
(0 ratings)
8.1
(0 ratings)
Usability
8.0
(0 ratings)
7.7
(0 ratings)
Support Rating
-
(0 ratings)
8.2
(0 ratings)
User Testimonials
Azure DatabricksKeras
Likelihood to Recommend
Having access to all databases and tables in one place is what has helped me and my team to function better. The in built functionality/access to SQL and Python is definitely an added bonus! The icing on the cake is the ability to export your data into an Excel spreadsheet for additional analysis. If you have less to no working knowledge of SQL or Python, its better to look at alternatives.
Read full review
I would recommend it for use when anyone wants to quickly develop a neural network. Or if a user is solving any machine learning problem that includes deep learning. And this kind of problem will be like image recognition, face recognition, doing some text analysis using deep learning which includes LSTM or some other algorithm.
Read full review
Pros
  • Consistently great performance when dealing with huge scale data with the help of spark architecture
  • Magic commands such as spark sql, pyspark, scala . This comes really handy in day to day work
  • Integration with other Azure services is super smooth and robust
Read full review
  • Implementing neural networks and deep learning models is easy with this.
  • Data processing is easy with Python and Keras. Keras helps a lot and has a good collection of functions to do data processing.
  • It has good integration with other devices like Android.
Read full review
Cons
  • Intuitive interface
  • Ease of use
  • Providing FAQ or QRGs
Read full review
  • I didn't face any issue so far.
  • The only thing, you can't modify everything in this. So it's not recommended for constructing highly optimised algorithms.
Read full review
Usability
Based on my extensive use of Azure Databricks for the past 3.5 years, it has evolved into a beautiful amalgamation of all the data domains and needs. From a data analyst, to a data engineer, to a data scientist, it jas got them all! Being language agnostic and focused on easy to use UI based control, it is a dream to use for every Data related personnel across all experience levels!
Read full review
The reason for giving this much rating. 1. It makes my job really easy and fast. 2. Strong community support. 3. Overall cost.
Read full review
Support Rating
No answers on this topic
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.
Read full review
Alternatives Considered
Against all the tools I have used, Azure Databricks is by far the most superior of them all! Why, you ask? The UI is modern, the features are never ending and they keep adding new features. And to quote Apple, "It just works!" Far ahead of the competition, the delta lakehouse platform also fares better than it counterparts of Iceberg implementation or a loosely bound Delta Lake implementation of Synapse
Read full review
As Keras is the high level API, so using Keras, we don't have to be bothered by the low level TensorFlow complexity, and we can reduce a lot coding and testing efforts.
Read full review
Return on Investment
  • The support team is amazing, they help you at every stage of the projects, from sales to delivery.
  • On a framework level, it has had an amazing impact and has reduced the clients overall data platform costs by a staggering 65%
  • There has been a 40% Manual work requirement on average for the clients when they move to Azure Databricks Data Platform
Read full review
  • It helped me in learning the basic concept of deep learning by having hands-on experience.
  • It has helped us to implement our NN with very little time.
  • It doesn't give you the whole power to customize your neural network. If you want that then you have to shift to TensorFLow
Read full review
ScreenShots