Good way to standardize Python-based developments & support for desktop users.
March 17, 2020

Good way to standardize Python-based developments & support for desktop users.

Juande Santander-Vela | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with Anaconda

The usage of Anaconda is not yet standard through the organization, but many people at my organization use it as the best way to create a standardized Python environment. In particular, the Miniconda distribution is preferred for deployment of Python-based containers, as it allows for a better, finer-grained installation in containers. For desktop users, the full Anaconda distribution is used, as it comes with several packages that are used throughout the organization: Astropy, NumPy, Matplotlib, Pandas, and others.
  • Management of custom environments
  • Support for standardizing deployments
  • Deployment in containers using Miniconda
  • Update of Conda packages is becoming slower. The 4.7 update was welcome, but seems to be regressing again.
  • Anaconda (and especially Miniconda) has simplified our deployment strategy.
Anaconda has 64-bit support in the community edition, and package management is more in line with the way we think.
There are a lot of materials allowing you to get self-service support with Anaconda. I have not tried any support tier for Anaconda.

Do you think Anaconda delivers good value for the price?

Yes

Are you happy with Anaconda's feature set?

Yes

Did Anaconda live up to sales and marketing promises?

Yes

Did implementation of Anaconda go as expected?

Yes

Would you buy Anaconda again?

Yes

Anaconda, and Miniconda, are easy to deploy, scientifically-ready Python distributions, especially well-suited for the fields of science, astronomy, and engineering. We are using Miniconda for finer-grained customization of environments in containers for deployment.

We are not using the customer supported version of Anaconda, and instead, we are relying on the community edition, based on the Open Source of all of our software. Hence, I am not evaluating Anaconda's support. Also, we are not making use as a company of the multi-language support in Anaconda, but I have tried the SciJava, R, and Julia support in Anaconda.

Anaconda Feature Ratings

Connect to Multiple Data Sources
9
Extend Existing Data Sources
9
Automatic Data Format Detection
Not Rated
MDM Integration
Not Rated
Visualization
9
Interactive Data Analysis
9
Interactive Data Cleaning and Enrichment
9
Data Transformations
9
Data Encryption
7
Built-in Processors
7
Multiple Model Development Languages and Tools
10
Automated Machine Learning
7
Single platform for multiple model development
9
Self-Service Model Delivery
Not Rated
Flexible Model Publishing Options
Not Rated
Security, Governance, and Cost Controls
Not Rated

Using Anaconda

ProsCons
Like to use
Relatively simple
Easy to use
Technical support not required
Well integrated
Consistent
Quick to learn
Convenient
Feel confident using
Familiar
None
  • Environment Update
  • Package Management
  • Managing non-standard channels
The interface is an easy to use command-line interface, or a GUI for launching and/or discovering different parts of the system.