Azure Databricks vs. Cloudera Data Science Workbench

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure Databricks
Score 8.5 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
Data Science Workbench
Score 6.7 out of 10
N/A
Cloudera Data Science Workbench enables secure self-service data science for the enterprise. It is a collaborative environment where developers can work with a variety of libraries and frameworks.N/A
Pricing
Azure DatabricksCloudera Data Science Workbench
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure DatabricksData Science Workbench
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 DatabricksCloudera Data Science Workbench
Features
Azure DatabricksCloudera Data Science Workbench
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Azure Databricks
7.0
3 Ratings
17% below category average
Cloudera Data Science Workbench
7.5
2 Ratings
10% below category average
Connect to Multiple Data Sources6.73 Ratings7.02 Ratings
Extend Existing Data Sources7.23 Ratings8.02 Ratings
Automatic Data Format Detection6.73 Ratings7.02 Ratings
MDM Integration7.42 Ratings8.02 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Azure Databricks
7.3
3 Ratings
15% below category average
Cloudera Data Science Workbench
7.6
2 Ratings
10% below category average
Visualization7.13 Ratings7.12 Ratings
Interactive Data Analysis7.53 Ratings8.02 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Azure Databricks
8.0
3 Ratings
2% below category average
Cloudera Data Science Workbench
7.8
2 Ratings
4% below category average
Interactive Data Cleaning and Enrichment7.03 Ratings7.02 Ratings
Data Transformations8.43 Ratings8.02 Ratings
Data Encryption9.63 Ratings8.02 Ratings
Built-in Processors7.13 Ratings8.02 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Azure Databricks
7.4
3 Ratings
12% below category average
Cloudera Data Science Workbench
7.6
2 Ratings
9% below category average
Multiple Model Development Languages and Tools5.13 Ratings8.02 Ratings
Automated Machine Learning8.43 Ratings7.01 Ratings
Single platform for multiple model development8.03 Ratings7.12 Ratings
Self-Service Model Delivery8.03 Ratings8.12 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Azure Databricks
7.9
3 Ratings
7% below category average
Cloudera Data Science Workbench
8.0
2 Ratings
6% below category average
Flexible Model Publishing Options7.43 Ratings8.12 Ratings
Security, Governance, and Cost Controls8.43 Ratings7.82 Ratings
Best Alternatives
Azure DatabricksCloudera Data Science Workbench
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 8.6 out of 10
Jupyter Notebook
Jupyter Notebook
Score 8.6 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
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User Ratings
Azure DatabricksCloudera Data Science Workbench
Likelihood to Recommend
9.7
(3 ratings)
9.0
(3 ratings)
Usability
8.0
(1 ratings)
-
(0 ratings)
Support Rating
-
(0 ratings)
7.9
(2 ratings)
User Testimonials
Azure DatabricksCloudera Data Science Workbench
Likelihood to Recommend
Microsoft
Centralised notebooks are out directly into production. This can lead to poorly engineered code. It is very good for fast queries and our data team are always able to provide what we ask for. It is a big cost to our business so it is important it runs efficiently and returns on our investment.
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Cloudera
Organizations which already implemented on-premise Hadoop based Cloudera Data Platform (CDH) for their Big Data warehouse architecture will definitely get more value from seamless integration of Cloudera Data Science Workbench (CDSW) with their existing CDH Platform. However, for organizations with hybrid (cloud and on-premise) data platform without prior implementation of CDH, implementing CDSW can be a challenge technically and financially.
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Pros
Microsoft
  • Data Processing and Transformations based on Spark
  • Delta Lakehouse when clubbed with an external cloud storage
  • Governance using Unity Catalog to unify IAM
  • Delta Live Tables is a product, which although relatively newer, has a great potential with the visuals of a pipeline.
Read full review
Cloudera
  • One single IDE (browser based application) that makes Scala, R, Python integrated under one tool
  • For larger organizations/teams, it lets you be self reliant
  • As it sits on your cluster, it has very easy access of all the data on the HDFS
  • Linking with Github is a very good way to keep the code versions intact
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Cons
Microsoft
  • Intuitive interface
  • Ease of use
  • Providing FAQ or QRGs
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Cloudera
  • Installation is difficult.
  • Upgrades are difficult.
  • Licensing options are not flexible.
Read full review
Usability
Microsoft
Great for what we use day to day and does what we need it to do. Cost management is not fully developed across the UX and gets expensive very quickly for developing projects. Integrated very well with our Microsoft stack and can be worked on collaboratively which works well for us.
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Cloudera
No answers on this topic
Support Rating
Microsoft
No answers on this topic
Cloudera
Cloudera Data Science Workbench has excellence online resources support such as documentation and examples. On top of that the enterprise license also comes with SLA on opening a ticket to Cloudera Services and support for complaint handling and troubleshooting by email or through a phone call. On top of that it also offers additional paid training services.
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Alternatives Considered
Microsoft
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
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Cloudera
Both the tools have similar features and have made it pretty easy to install/deploy/use. Depending on your existing platform (Cloudera vs. Azure) you need to pick the Workbench. Another observation is that Cloudera has better support where you can get feedback on your questions pretty fast (unlike MS). As its a new product, I expect MS to be more efficient in handling customers questions.
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Return on Investment
Microsoft
  • Helped reduce time for collecting data
  • Reduced cost in maintaining multiple data sources
  • Access for multiple users and management of users/data in a single platform
Read full review
Cloudera
  • Paid off for demonstration purposes.
Read full review
ScreenShots