H2O.ai vs. Spotfire Data Science

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
H2O.ai
Score 6.8 out of 10
N/A
An open-source end-to-end GenAI platform for air-gapped, on-premises or cloud VPC deployments. Users can Query and summarize documents or just chat with local private GPT LLMs using h2oGPT, an Apache V2 open-source project. And the commercially available Enterprise h2oGPTe provides information retrieval on internal data, privately hosts LLMs, and secures data.N/A
Spotfire Data Science
Score 8.7 out of 10
N/A
Spotfire Data Science (formerly TIBCO Data Science) is a comprehensive platform for operationalizing data science, allowing users to scale data science across an organization to solve complex challenges faster and speed innovation. It is designed to enable data scientists to create innovative solutions using the latest machine learning techniques and open source developments. Create ML pipelines using a point-and-click UI or code. Orchestrate analytics using the tools, languages, and any…N/A
Pricing
H2O.aiSpotfire Data Science
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
H2O.aiSpotfire Data Science
Free Trial
NoYes
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
H2O.aiSpotfire Data Science
Top Pros
Top Cons
Features
H2O.aiSpotfire Data Science
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
H2O.ai
-
Ratings
Spotfire Data Science
9.1
4 Ratings
7% above category average
Connect to Multiple Data Sources00 Ratings9.14 Ratings
Extend Existing Data Sources00 Ratings9.14 Ratings
Automatic Data Format Detection00 Ratings9.14 Ratings
MDM Integration00 Ratings9.14 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
H2O.ai
-
Ratings
Spotfire Data Science
9.1
4 Ratings
8% above category average
Visualization00 Ratings9.14 Ratings
Interactive Data Analysis00 Ratings9.14 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
H2O.ai
-
Ratings
Spotfire Data Science
9.0
4 Ratings
9% above category average
Interactive Data Cleaning and Enrichment00 Ratings9.14 Ratings
Data Transformations00 Ratings9.14 Ratings
Data Encryption00 Ratings8.93 Ratings
Built-in Processors00 Ratings9.14 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
H2O.ai
-
Ratings
Spotfire Data Science
9.1
4 Ratings
7% above category average
Multiple Model Development Languages and Tools00 Ratings9.14 Ratings
Automated Machine Learning00 Ratings9.14 Ratings
Single platform for multiple model development00 Ratings9.14 Ratings
Self-Service Model Delivery00 Ratings9.14 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
H2O.ai
-
Ratings
Spotfire Data Science
9.1
4 Ratings
6% above category average
Flexible Model Publishing Options00 Ratings9.14 Ratings
Security, Governance, and Cost Controls00 Ratings9.14 Ratings
Best Alternatives
H2O.aiSpotfire Data Science
Small Businesses
Astra DB
Astra DB
Score 8.3 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Astra DB
Astra DB
Score 8.3 out of 10
Mathematica
Mathematica
Score 8.3 out of 10
Enterprises
Dataiku
Dataiku
Score 7.9 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
H2O.aiSpotfire Data Science
Likelihood to Recommend
8.1
(3 ratings)
9.0
(16 ratings)
Likelihood to Renew
-
(0 ratings)
6.4
(1 ratings)
Support Rating
9.0
(1 ratings)
-
(0 ratings)
User Testimonials
H2O.aiSpotfire Data Science
Likelihood to Recommend
H2O.ai
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.
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Spotfire
If you have an analytics department, Data Science is perfect for making analyses quicker. Data Science works well for web querying, automating analyses, sharing advanced analyses with others, and performing lots of other advanced analytical processes. Data Science is not a good fit if the analytics you do is stuff that Excel can do. The software is powerful, with lots of features, and unless you actually plan on using those features, it's not worth paying for.
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Pros
H2O.ai
  • 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
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Spotfire
  • It has a great user interface, easy to navigate and learn on the fly.
  • There are lots of great options for data organization and analysis! Makes it a handy tool for presentations as well.
  • A collaborative ability is highly valued for my company where we often work from home or on site. Being able to share the data with those in the office so multiple people can look at it is a great tool!
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Cons
H2O.ai
  • Better documentation
  • Improve the Visual presentations including charting etc
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Spotfire
  • Unfortunately, some functionality is hidden per upgrade to other versions. Feel data mining functionality would be useful, but not budget for software. At the current price point, would have expected more (such as Mathematica breadth of functionality for one price).
  • It is light on optimization capability.
  • Slow when considering very large datasets, performing things such as distribution identification
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Likelihood to Renew
H2O.ai
No answers on this topic
Spotfire
The company is hesitant to spend this much on software. They are primarily an engineering firm, and they don't understand the use of analytical software for environmental professionals.
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Support Rating
H2O.ai
The overall experience I have with H2O is really awesome, even with its cost effectiveness.
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Spotfire
No answers on this topic
Alternatives Considered
H2O.ai
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.
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Spotfire
I prefer Spotfire Data Science's approach. It is more natural and fits the way I think. I prefer to use Spotfire Data Science's VB for writing macros. It is real code, meaning that I do not need to trick the software to do what I need and there are no implied loops over solving simple problems. The graphs are publication quality and can be edited by hand or using a macro if I am building hundreds of them. Spotfire Data Science had a user-friendly approach to building lengthy data processing streams (in its workspaces). It is just so fast for analyzing a dataset that you have never seen before and efficient for ongoing work on the same data.
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Return on Investment
H2O.ai
  • 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
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Spotfire
  • Our company has had the program for less than 1 year. We don't expected a positive return this year. The goal is for Data Science to led to defined projects by the end of the end of the year and implementation in the following two. Overall, we are planning on 4 years to fully recoup the cost of the software and the cost of implementing identified projects.
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ScreenShots

Spotfire Data Science Screenshots

Screenshot of Reusable Workspace TemplateScreenshot of AutoML - Create Editable Workflows for Feature Selection/Generation, Model Creation/Selection, Hyperparameter TuingScreenshot of Interactive DashboardScreenshot of Orchestrate Analytics across Amazon, Google, and Microsoft