# H2O Reviews **Vendor:** H2O.ai **Category:** [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms) **Average Rating:** 4.5/5.0 **Total Reviews:** 24 ## About H2O H2O.ai is the leading AI Cloud company, on a mission to democratize AI and drive an open AI movement around the world. They focus on drawing insights from structured and unstructured data like video and documents with their award-winning products like Hydrogen Torch and Document AI. Customers use the H2O AI Cloud to rapidly solve complex business problems and accelerate the discovery of new ideas. H2O.ai is the trusted AI provider to more than 20,000 global organizations, millions of data scientists and over half of the Fortune 500, including AT&T, Commonwealth Bank of Australia, Citi, GlaxoSmithKline, Hitachi, Kaiser Permanente, Procter & Gamble, PayPal, PwC, Reckitt, Unilever, Goldman Sachs, NVIDIA, and Wells Fargo are not only customers and partners, but strategic investors in the company. More than 30 Kaggle Grandmasters (the community of best-in-the-world machine learning practitioners and data scientists) are makers at H2O.ai. A strong AI for Good ethos to make the world a better place and Responsible AI drive the company’s purpose. Please join our movement at www.h2o.ai. H2O.ai offers enterprise customers with multiple platforms for AI and machine learning, including the open source distributed machine learning platform H2O-3, automatic machine learning platform H2O Driverless AI, and the recently announced H2O Q, an AI platform for business users: H2O-3 is an open source, scalable and distributed in-memory AI and machine learning platform. H2O-3 also has a strong AutoML functionality and supports the most widely used statistical and machine learning algorithms including gradient boosted machines, generalized linear models, deep learning, XGBoost and more. H2O Driverless AI empowers data scientists to work on projects faster and more efficiently by using automation to accomplish tasks quickly with automatic feature engineering, model tuning, model tuning, model selection, model validation and machine learning interpretability, custom recipes, time-series and automatic deployment pipeline generation for model scoring. H2O Q is a new AI platform that provides the essential building blocks to make AI apps and will bring the power of AI to millions of business users. It delivers automatic insights and predictions for “in the moment” business questions and is ideal for data analysts, citizen data scientists and all business users. ## H2O Reviews ### 1. Excellent framework and application **Rating:** 5.0/5.0 stars **Reviewed by:** Marc S. | CEO, Small-Business (50 or fewer emp.) **Reviewed Date:** January 19, 2021 **What do you like best about H2O?** Excellent support for commercial product Driverless AI. Rapid iteration. Performance is generally better than one can be achieved in code. **What do you dislike about H2O?** Actually nothing. The combination of proprietary and open source tools, Driverless AI and H2O, provide tools across a full range of use cases. **Recommendations to others considering H2O:** Take advantage of the 30 day trial. **What problems is H2O solving and how is that benefiting you?** We work in both financial services and biological research. ### 2. Good Automl software **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Oil & Energy | Small-Business (50 or fewer emp.) **Reviewed Date:** December 16, 2021 **What do you like best about H2O?** The web front end known as flow is really easy to use. It can be use to quickly create machine learning models. **What do you dislike about H2O?** The complex machine learning model overfit the data. This is especially true when the data set is small. **What problems is H2O solving and how is that benefiting you?** Trying to forecast prices using the regression models. It's very quick to test out new models. ### 3. Workflows for quick ML prototyping **Rating:** 4.5/5.0 stars **Reviewed by:** Renzo S. | Small-Business (50 or fewer emp.) **Reviewed Date:** November 16, 2020 **What do you like best about H2O?** They developed top-quality open source tools, including the H2O-3 and AutoML families. I do not have a license for their Driverless AI, but my experience with it through tutorials and other demos has been superb. I should mention that their efforts to develop frameworks for ML interpretability are spot on, and their learning center is shaping up as a valuable resource to the community in general. The interfaces with R and Python enable a smooth transition of pre-existing workflows into the H2O framework. **What do you dislike about H2O?** Somewhat cryptic debugging msgs in H2O-3. They support specific packages for manipulating data (data.table in R, datataable in Python) for the sake of speed and big data maneuverability, although many users may find this limiting. Driverless AI may not be affordable to the small fish in the pond. **Recommendations to others considering H2O:** One should leverage all the resources available to test their products before buying. **What problems is H2O solving and how is that benefiting you?** I have mostly used their AutoML to build quick ML/AI prototype solutions in different domains. ### 4. Driverless AI application for Auomated Machine Learning and Data Analytics **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Electrical/Electronic Manufacturing | Small-Business (50 or fewer emp.) **Reviewed Date:** April 14, 2020 **What do you like best about H2O?** Easy to use with good UI design and automated ML function. Driverless AI has strong capability on the auto feature engineering and system visualization. The auto feature engineering has supported different machine learning algorithm (Random Forest, Decision Tree, Neural Network, Deep Learning, etc.) and feature parameter tuning (accuracy, time, system computing etc.) The system also helps user to reduce time and efforts for hyparemeter tuning and compare the model with different settings. This will optimize the process and provide the most efficient model for prediction in classification or regression domain. Besides, Driverless AI also has good UI design and visualization. The UI also supports end user to quickly import data, visualize data in different categories, as well as check on the system running and performance during the Auto ML process. The end user could also observe experiment summary and accuracy matrix, as well as model comparison in term of accuracy. In addition, Driverless AI also supports the AI Interpretation to explain on the model and performance. This function is very helpful to end user for understanding the Machine Learning blackbox, as well as management team for decision making based on extensive information. **What do you dislike about H2O?** It is great if Driverless AI could support deployment for edge computing, which is common in IoT world. The edge computing will require efficient computing and good accuracy with AutoML algorithm. This will help much the customer for deployment. **Recommendations to others considering H2O:** Yes, H2O.ai DriverlessAI is a good AutoML platform for company, which does not have Data Scientist. **What problems is H2O solving and how is that benefiting you?** Data analytics for predictive maintenance. It could make easy-to-use for system operator. ### 5. A very good experience with Machine Learning **Rating:** 5.0/5.0 stars **Reviewed by:** Rafael P. | Lecturer, Enterprise (> 1000 emp.) **Reviewed Date:** July 13, 2020 **What do you like best about H2O?** AutoML is a great product. They have other ones, but AutoML is the most impressive. **What do you dislike about H2O?** Nothing, maybe the integration with Spark could be improved but only in little details. **Recommendations to others considering H2O:** It's an amazing set of tools, easing the use of machine learning and giving a lot of advances to write & discover models. **What problems is H2O solving and how is that benefiting you?** Forecasting models and finding for best algorithms for my datasets ### 6. h2o is my personal data scientist **Rating:** 5.0/5.0 stars **Reviewed by:** Jiook C. | Assistant Professor, Small-Business (50 or fewer emp.) **Reviewed Date:** November 13, 2020 **What do you like best about H2O?** h2o offers a well validated, fully automated, rigorous machine learning pipeline including state of the art model interpretation allowing for prediction and inferences. **What do you dislike about H2O?** i have nothing dislike about h2o's products. **What problems is H2O solving and how is that benefiting you?** my scientific questions involve biomedicine, neuroscience, and psychology ### 7. Great Machine Learning Framework **Rating:** 5.0/5.0 stars **Reviewed by:** Binesh S. | Mid-Market (51-1000 emp.) **Reviewed Date:** July 27, 2020 **What do you like best about H2O?** The ability to try out multiple models with a few lines of the code is the greatest benefit **What do you dislike about H2O?** H20 does a good job in abstraction of underlying transformation and tuning steps, which could be a bit challenging **Recommendations to others considering H2O:** Great framework **What problems is H2O solving and how is that benefiting you?** 1. Policy Lapse Predictor - the biggest benefit is the automation of model tuning ### 8. H2O.ai is a great tool who wants to build a scalable and interpretable machine learning pipeline. **Rating:** 5.0/5.0 stars **Reviewed by:** Young Hoon K. | Enterprise (> 1000 emp.) **Reviewed Date:** April 14, 2020 **What do you like best about H2O?** I find it most helpful that it provides GUI for users to estimate how long the model will run as well as the water meter showing how the resources are used along the modeling process. **What do you dislike about H2O?** H2O Frames have very limited data processing options compared to python pandas or pyspark dataframes. If we can have more data maneuverability, I think it would help a lot. **Recommendations to others considering H2O:** I believe it is a great tool for those who are looking to establish ML pipeline with ease. **What problems is H2O solving and how is that benefiting you?** Purchase forecasting, employee estimation, etc. ### 9. Great Product **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Capital Markets | Small-Business (50 or fewer emp.) **Reviewed Date:** July 24, 2020 **What do you like best about H2O?** The best part of H2O.ai is its ease of use and seamless UI. **What do you dislike about H2O?** One downside of H2O.ai is, as with many services, its bugs which do not return human-readable debugging statements. **What problems is H2O solving and how is that benefiting you?** I have used H2O for time-series data, and stock market prediction. ### 10. Accessible ML **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Research | Small-Business (50 or fewer emp.) **Reviewed Date:** September 22, 2020 **What do you like best about H2O?** Clean interface through Driverless AI and variety of analyses **What do you dislike about H2O?** Better instructions would be helpful, as would clearer tutorials **What problems is H2O solving and how is that benefiting you?** Need for adaptable ML analyses. Plug and play. ### 11. Great ML framework **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Non-Profit Organization Management | Small-Business (50 or fewer emp.) **Reviewed Date:** July 24, 2020 **What do you like best about H2O?** This is a cross-platform, integrated framework for ML that is continuing to evolve with topics important to data scientists. **What do you dislike about H2O?** Developing support for a wide range of NLP preprocessing **What problems is H2O solving and how is that benefiting you?** Problems in academic research and healthcare ### 12. Its superb **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Banking | Small-Business (50 or fewer emp.) **Reviewed Date:** August 06, 2020 **What do you like best about H2O?** Ease of use and its high performance for building models **What do you dislike about H2O?** Does not support data cleaning and some algorithms **What problems is H2O solving and how is that benefiting you?** Used to solve complex machine learning problems ### 13. Good and easy **Rating:** 4.0/5.0 stars **Reviewed by:** David Isaac M. | Senior Data Scientist, Small-Business (50 or fewer emp.) **Reviewed Date:** April 14, 2020 **What do you like best about H2O?** Streamlining our process for generating and deploying machine learning models. **What do you dislike about H2O?** it its not much friendly when you try to automatize process **Recommendations to others considering H2O:** Streamlining our process for generating and deploying machine learning models. **What problems is H2O solving and how is that benefiting you?** machine learning models ### 14. Excellent machine learning tools **Rating:** 5.0/5.0 stars **Reviewed by:** Marc S. | Founder and CEO, Small-Business (50 or fewer emp.) **Reviewed Date:** February 20, 2020 **What do you like best about H2O?** Good integration between development and production. Simple and powerful visual interface to complex backend. Very rapid iteration of products, continuous improvement. **What do you dislike about H2O?** Price is high for closed source product, Driverless AI. It's worth it if you have a serious application, but the cost is an impediment to early adoption. **What problems is H2O solving and how is that benefiting you?** Streamlining our process for generating and deploying machine learning models. ### 15. Excellent software - great addition to a data science team **Rating:** 5.0/5.0 stars **Reviewed by:** Marom M. | Mid-Market (51-1000 emp.) **Reviewed Date:** April 13, 2020 **What do you like best about H2O?** Excellent support. Useful and reliable software. Easy to deploy. **What do you dislike about H2O?** No issues. The software works very well. **What problems is H2O solving and how is that benefiting you?** Predictive analytics in credit and marketing. Software works well in our systems. ### 16. Great AI product **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Marketing and Advertising | Mid-Market (51-1000 emp.) **Reviewed Date:** February 20, 2020 **What do you like best about H2O?** Many model types, great cluster performance, easy to setup **What do you dislike about H2O?** Would like to see SVM , Gaussian processes, and some time series models **What problems is H2O solving and how is that benefiting you?** AdTech modeling. Can create complex models on data sets with a billion rows. Much faster turnaround time ### 17. Good Customer support **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Retail | Enterprise (> 1000 emp.) **Reviewed Date:** April 21, 2020 **What do you like best about H2O?** Being a user I really enjoyed the support and dedication that team shown to help us is really great! **What do you dislike about H2O?** H2O should stay ahead of the curve to give support to new technology stacks like databricks. **What problems is H2O solving and how is that benefiting you?** We use H2O for our model building ### 18. Expanding AI Product with Excellent Support **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Insurance | Enterprise (> 1000 emp.) **Reviewed Date:** February 21, 2020 **What do you like best about H2O?** The predictive modeling and machine learning capabilities of this product are top-notch along with their support and training. **What do you dislike about H2O?** Documentation in general can be improved. **Recommendations to others considering H2O:** Ask for H2O's training before you use the software - you'll have a much better time. **What problems is H2O solving and how is that benefiting you?** We have been able to create features previously undetected and build more accurate prediction models. ### 19. DriverlessAI **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Industrial Automation | Small-Business (50 or fewer emp.) **Reviewed Date:** February 20, 2020 **What do you like best about H2O?** H2O provides DriverlessAI for an efficient AutoML platform and effective UI tools for data scientist and end-user. **What do you dislike about H2O?** DriverlessAI could provide more use-cases in Manufacturing domain. **What problems is H2O solving and how is that benefiting you?** We are working on Predictive Maintenance and Analytics, which could be potentially used for Manufacturing and Factory. ### 20. Very easy to use **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Marketing and Advertising | Enterprise (> 1000 emp.) **Reviewed Date:** November 07, 2018 **What do you like best about H2O?** the tool itself is very intuitive and easy to use. installation is quick. porting to R and Python options are nice to haves. **What do you dislike about H2O?** there isn't much visibility into how h2o is better in using each algorithm. **What problems is H2O solving and how is that benefiting you?** machine learning. expediting the process and replicating the process. ### 21. Quick Prototyping **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** October 31, 2018 **What do you like best about H2O?** It's a great tool for really quick prototyping. Easy to build pretty complex models fast and test the results on datasets. It allows you to test various models before you decide which you want to fine tune. Good python support as well. **What do you dislike about H2O?** Documentation can be improved especially with how to integrate with python. **What problems is H2O solving and how is that benefiting you?** Prototypes for ML application in software engineering. ### 22. Popular machine learning platform **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Media Production | Small-Business (50 or fewer emp.) **Reviewed Date:** November 24, 2018 **What do you like best about H2O?** I met h2o.ai with Gartner Magic Quadrant. It's great ML platform with it's extensive built-in library. **What do you dislike about H2O?** Price architecture is confusing a bit. Also we'd like to see more use cases and customer stories for marketing applications. **What problems is H2O solving and how is that benefiting you?** We evaluated churn prediction algorithms to score our customer database. ### 23. Great platform for R **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Retail | Enterprise (> 1000 emp.) **Reviewed Date:** November 28, 2018 **What do you like best about H2O?** It's a great platform with R library. Library functions saved our time. **What do you dislike about H2O?** It needs more R libraries on planning management. **What problems is H2O solving and how is that benefiting you?** We've used H20.ai for assortment optimization. ### 24. Good but a little disappointed **Rating:** 3.0/5.0 stars **Reviewed by:** Laurry P. | Consultant en gestion informatique, Mid-Market (51-1000 emp.) **Reviewed Date:** January 08, 2018 **What do you like best about H2O?** The steam AI engine: an end-to-end platform that streamlines the entire process of creating and deploying intelligent applications it is fast **What do you dislike about H2O?** Certain bugs and slowdowns that are very annoying **Recommendations to others considering H2O:** the service **What problems is H2O solving and how is that benefiting you?** His work ## H2O Discussions - [How does h2o AI make money?](https://www.g2.com/discussions/how-does-h2o-ai-make-money) - [How much does h2o Ai cost?](https://www.g2.com/discussions/how-much-does-h2o-ai-cost) - [Why is h2o AI?](https://www.g2.com/discussions/why-is-h2o-ai) - [Is h2o AI free?](https://www.g2.com/discussions/is-h2o-ai-free) - [View H2O pricing details and edition comparison](https://www.g2.com/products/h2o/reviews?section=pricing&secure%5Bexpires_at%5D=2026-06-03+13%3A08%3A50+-0500&secure%5Bsession_id%5D=9aae67b4-ea0e-4bb8-98fe-59c45bf89f54&secure%5Btoken%5D=8a760bc71679bc778a1b536abf58557fecee93a97a8501759c7b34f3c40aeb31&format=llm_user) ## H2O Features **System** - Data Ingestion & Wrangling **Scalability and Performance - Generative AI Infrastructure** - AI High Availability - AI Model Training Scalability - AI Inference Speed **Core Functionality - Artificial Neural Network** - Neural Network Training - Neural Network Testing - Model Evaluation - Compliance **Statistical Tool** - Scripting - Data Mining - Algorithms **Model Development** - Language Support - Drag and Drop - Pre-Built Algorithms - Model Training **Model Development** - Feature Engineering **Cost and Efficiency - Generative AI Infrastructure** - AI Cost per API Call - AI Resource Allocation Flexibility - AI Energy Efficiency **Data Handling - Artificial Neural Network** - Data Integration - Data Preprocessing **Data Analysis** - Analysis - Data Interaction **Machine/Deep Learning Services** - Computer Vision - Natural Language Processing - Natural Language Generation - Artificial Neural Networks **Machine/Deep Learning Services** - Natural Language Understanding - Deep Learning **Integration and Extensibility - Generative AI Infrastructure** - AI Multi-cloud Support - AI Data Pipeline Integration - AI API Support and Flexibility **Performance - Artificial Neural Network** - Model Optimization - Scalability **Decision Making** - Modeling - Data Visualizations - Report Generation - Data Unification **Deployment** - Managed Service - Application - Scalability **Security and Compliance - Generative AI Infrastructure** - AI GDPR and Regulatory Compliance - AI Role-based Access Control - AI Data Encryption **Usability - Artificial Neural Network** - User Interface - Documentation & Support - Customizability **Generative AI** - AI Text Generation - AI Text Summarization **Generative AI** - AI Text Generation - AI Text Summarization - AI Text-to-Image **Usability and Support - Generative AI Infrastructure** - AI Documentation Quality - AI Community Activity **Advanced Features - Artificial Neural Network** - Deep Learning Capabilities - Transfer Learning - Real-Time Processing - Automated Model Tuning - Visualization Tools **Agentic AI - Data Science and Machine Learning Platforms** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making **Agentic AI - Artificial Neural Network** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making ## Top H2O Alternatives - [Dataiku](https://www.g2.com/products/dataiku/reviews) - 4.4/5.0 (189 reviews) - [Altair AI Studio](https://www.g2.com/products/rapidminer-studio/reviews) - 4.6/5.0 (493 reviews) - [Amazon SageMaker](https://www.g2.com/products/amazon-sagemaker/reviews) - 4.2/5.0 (51 reviews)