What users are saying about
51 Ratings
51 Ratings
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Score 8.6 out of 101
13 Ratings
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Score 7.5 out of 101

Likelihood to Recommend

Anaconda

Anaconda is great for academic and private organizations that cannot afford more expensive Python/R package managers. Also, it is more appropriate for intermediate to advanced Python users--Anaconda can be somewhat frustrating for beginners, as it takes some practice to get comfortable with the workflow. I find it particularly useful for working in teams, because if everyone uses the same package manager, it is easier to troubleshoot issues and makes for reproducible research. For wealthier organizations, a premium package management system (with tech support) would be ideal. Anaconda is also great for people working independently on code development.
Maike Holthuijzen profile photo

Data Science Workbench

  • If you already have a Cloudera partnership and a cluster, having this is a no brainer.
  • It integrates well with your existing ecosystem and it immediately starts working on projects, accessing full datasets and share analysis and results.
  • With the inclusion of Kubernetes, CPU and memory across worker nodes can be managed effectively.
Bharadwaj (Brad) Chivukula profile photo

Feature Rating Comparison

Platform Connectivity

Anaconda
7.0
Data Science Workbench
7.0
Connect to Multiple Data Sources
Anaconda
10.0
Data Science Workbench
6.0
Extend Existing Data Sources
Anaconda
8.0
Data Science Workbench
7.0
Automatic Data Format Detection
Anaconda
3.0
Data Science Workbench
7.0
MDM Integration
Anaconda
Data Science Workbench
8.0

Data Exploration

Anaconda
7.5
Data Science Workbench
9.0
Visualization
Anaconda
8.0
Data Science Workbench
9.0
Interactive Data Analysis
Anaconda
7.0
Data Science Workbench
9.0

Data Preparation

Anaconda
7.5
Data Science Workbench
7.8
Interactive Data Cleaning and Enrichment
Anaconda
8.0
Data Science Workbench
8.0
Data Transformations
Anaconda
9.0
Data Science Workbench
8.0
Data Encryption
Anaconda
6.0
Data Science Workbench
8.0
Built-in Processors
Anaconda
7.0
Data Science Workbench
7.0

Platform Data Modeling

Anaconda
8.1
Data Science Workbench
9.7
Multiple Model Development Languages and Tools
Anaconda
10.0
Data Science Workbench
9.0
Automated Machine Learning
Anaconda
6.5
Data Science Workbench
Single platform for multiple model development
Anaconda
8.5
Data Science Workbench
10.0
Self-Service Model Delivery
Anaconda
7.5
Data Science Workbench
10.0

Model Deployment

Anaconda
6.5
Data Science Workbench
7.0
Flexible Model Publishing Options
Anaconda
7.0
Data Science Workbench
10.0
Security, Governance, and Cost Controls
Anaconda
6.0
Data Science Workbench
4.0

Pros

Anaconda

  • Clear install story. There are a lot of ways to install python. There's only one way to install anaconda. This makes teaching and standardizing much easier.
  • Batteries included. It's easy to install things in python, but anaconda ships with most of what you need out of the box. This helps with standardization and reproducibility.
  • Good integrations with Jupyter and other visual tools. Jupyter is really convenient when learning various python packages. Anaconda makes these tools easy to launch and to use.
Matthew Deakyne profile photo

Data Science Workbench

  • The ability to use multiple languages.
  • GitHub integration.
  • Scalable.
No photo available

Cons

Anaconda

  • Although some other users mentioned the installation is "simple", we did encounter some challenge in a highly controlled environment (due to security reasons).
  • Jupyter Notebook is extremely slow when the client/server side of the network's speed/bandwidth is not balanced.
  • Bootstrapping Anaconda takes too long, sometimes I even started doubting it would respond any more.
  • If there are extra python packages you need but are not by default installed by Anaconda, then some efforts will be required to figure out how to put them in the right place.
No photo available

Data Science Workbench

  • Not as great as RStudio; lacks some features when compared with it
  • It is quite simple still (because its very early in its initiative), and companies may want to wait until they see a more developed product
Bharadwaj (Brad) Chivukula profile photo

Likelihood to Renew

Anaconda

Anaconda 7.0
Based on 1 answer
It's really good at data processing, but needs to grow more in publishing in a way that a non-programmer can interact with. It also introduces confusion for programmers that are familiar with normal Python processes which are slightly different in Anaconda such as virtualenvs.
Matthew Deakyne profile photo

Data Science Workbench

No score
No answers yet
No answers on this topic

Usability

Anaconda

Anaconda 8.0
Based on 1 answer
It's really good at installing and getting started. It's less usable and configurable after that. If you stay in the ecosystem, and don't know how to Python any other way - it works really well.
Matthew Deakyne profile photo

Data Science Workbench

No score
No answers yet
No answers on this topic

Support

Anaconda

No score
No answers yet
No answers on this topic

Data Science Workbench

Data Science Workbench 5.0
Based on 1 answer
It is expensive and difficult to install and maintain.
No photo available

Alternatives Considered

Anaconda

ANACONDA VS Alteryx Analytics: Even though I find Alteryx to be an excellent tool for managing extremely massive data, Anaconda is much better and easy for analytics.Anaconda VS. MicroStrategy Analytics: Compared with Anaconda, MicroStrategy Analytics is very difficult to use and counter-intuitiveAnaconda VS. Power BI For Office 365: One of the main advantages of BI for Office 364 is its capacity to data connectivity. However, it's very hard to edit data connections, once BI for Office is deployed in other platforms
Mauricio Quiroga-Pascal Ortega profile photo

Data Science Workbench

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.
Bharadwaj (Brad) Chivukula profile photo

Return on Investment

Anaconda

  • We can get any new employee set-up on Python for Machine learning in minutes, without any assistance from IT. That's real $ savings.
  • We started to experiment with Machine Learning a lot more, which leads to creating new projects which can have a tremendous impact on the business.
No photo available

Data Science Workbench

  • Paid off for demonstration purposes.
No photo available

Pricing Details

Anaconda

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Data Science Workbench

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

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