What users are saying about

Anaconda

Top Rated
33 Ratings

Anaconda

Top Rated
33 Ratings
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Score 8.8 out of 101

Data Science Workbench

10 Ratings
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Score 7.4 out of 101

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Likelihood to Recommend

Anaconda

If your organization is reliant on Machine Learning to solve real world business problems, Anaconda is very well suited for that need. It can be a bit of a pain to install all the necessary dependencies for Python to do Machine Learning. Anaconda takes care of all the installation of appropriate libraries. If you're organization is reliant on GitHub or other code repositories, it's a bit cumbersome to have that in Anaconda, so it might not be the solution for you.
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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

Pros

  • The most useful thing is the Jupyter notebook that Anaconda has inside the platform. You can use your browser to manage them and launch everything from your file system.
  • Anaconda exists for Python 2 and Python 3. So, you can use it despite which Python you use.
  • It's very easy to install, and it's multiplatform (Windows, OS X, Linux).
  • Friendly manage of Python packages.
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  • 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
Bharadwaj (Brad) Chivukula profile photo

Cons

  • Some Python packages are not included to Anaconda, so you have to install them using different ways, like using pip, for example.
  • Sometimes you get stuck because Anaconda still have some little bugs.
  • Anaconda is a little slow when it's initializing.
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  • 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

Alternatives Considered

Simple story. I tried both. Canopy felt somehow unintuitive to use.
Alexander Lubyansky profile photo
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

  • We save a lot of programming time, since all the add-ons are in the same environment.
  • Being multiplatform, Anaconda is perfect for work teams with many people, since it supports all operating systems.
  • The only negative thing that can happen is that at first, the way of working in Anaconda can be a bit confusing. Once passed the learning period, its daily use is very comfortable.
Alejandro Daniel Copati profile photo
  • As the tool itself can access all the HDFS, Spark data easily, the wait time between teams has reduced
  • Installation was a breeze, and ramp up time was fairly easy
Bharadwaj (Brad) Chivukula profile photo

Pricing Details

Anaconda

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

Data Science Workbench

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