What users are saying about
51 Ratings
6 Ratings
51 Ratings
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Score 8.6 out of 101
6 Ratings
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Score 9.1 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

H2O

Most suited if in little time you wanted to build and train a model. Then, H2O makes life very simple. It has support with R, Python and Java, so no programming dependency is required to use it. It's very simple to use.If you want to modify or tweak your ML algorithm then H2O is not suitable. You can't develop a model from scratch.
No photo available

Feature Rating Comparison

Platform Connectivity

Anaconda
7.0
H2O
8.0
Connect to Multiple Data Sources
Anaconda
10.0
H2O
8.0
Extend Existing Data Sources
Anaconda
8.0
H2O
Automatic Data Format Detection
Anaconda
3.0
H2O
8.0

Data Exploration

Anaconda
7.5
H2O
8.5
Visualization
Anaconda
8.0
H2O
8.0
Interactive Data Analysis
Anaconda
7.0
H2O
9.0

Data Preparation

Anaconda
7.5
H2O
9.3
Interactive Data Cleaning and Enrichment
Anaconda
8.0
H2O
10.0
Data Transformations
Anaconda
9.0
H2O
9.0
Data Encryption
Anaconda
6.0
H2O
Built-in Processors
Anaconda
7.0
H2O
9.0

Platform Data Modeling

Anaconda
8.1
H2O
10.0
Multiple Model Development Languages and Tools
Anaconda
10.0
H2O
10.0
Automated Machine Learning
Anaconda
6.5
H2O
10.0
Single platform for multiple model development
Anaconda
8.5
H2O
10.0
Self-Service Model Delivery
Anaconda
7.5
H2O
10.0

Model Deployment

Anaconda
6.5
H2O
9.0
Flexible Model Publishing Options
Anaconda
7.0
H2O
10.0
Security, Governance, and Cost Controls
Anaconda
6.0
H2O
8.0

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

H2O

  • Excellent analytical and prediction tool
  • In the beginning, usage of H20 Flow in Web UI enables quick development and sharing of the analytical model
  • Readily available algorithms, easy to use in your analytical projects
  • Faster than Python scikit learn (in machine learning supervised learning area)
  • It can be accessed (run) from Python, not only JAVA etc.
  • Well documented and suitable for fast training or self studying
  • In the beginning, one can use the clickable Flow interface (WEB UI) and later move to a Python console. There is then no need to click in H20 Flow
  • It can be used as open source
Viktor Mulac profile photo

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

H2O

  • Better documentation
  • Improve the Visual presentations including charting etc
No photo available

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

H2O

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

H2O

No score
No answers yet
No answers on this topic

Support

Anaconda

No score
No answers yet
No answers on this topic

H2O

H2O 9.0
Based on 1 answer
The overall experience I have with H2O is really awesome, even with its cost effectiveness.
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

H2O

Both are open source (though H2O only up to some level). Both comprise of deep learning, but H2O is not focused directly on deep learning, while Tensor Flow has a "laser" focus on deep learning. H2O is also more focused on scalability. H2O should be looked at not as a competitor but rather a complementary tool. The use case is usually not only about the algorithms, but also about the data model and data logistics and accessibility. H2O is more accessible due to its UI. Also, both can be accessed from Python. The community around TensorFlow seems larger than that of H2O.
Viktor Mulac 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

H2O

  • Positive impact: saving in infrastructure expenses - compared to other bulky tools this costs a fraction
  • Positive impact: ability to get quick fixes from H2O when problems arise - compared to waiting for several months/years for new releases from other vendors
  • Positive impact: Access to H2O core team and able to get features that are needed for our business quickly added to the core H2O product
No photo available

Pricing Details

Anaconda

General

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

H2O

General

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

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