What users are saying about
50 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener'>trScore algorithm: Learn more.</a>Score 8.7 out of 100
Based on 50 reviews and ratings
9 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener'>trScore algorithm: Learn more.</a>Score 8.7 out of 100
Based on 9 reviews and ratings
Feature Set Ratings
Platform Connectivity
Databricks Lakehouse Platform
Feature Set Not Supported
N/A

8.0
H2O
80%
H2O ranks higher in 2/2 features
H2O ranks higher in 2/2 features
Connect to Multiple Data Sources
N/A
0 Ratings

8.0
80%
1 Rating
Automatic Data Format Detection
N/A
0 Ratings

8.0
80%
1 Rating
Data Exploration
Databricks Lakehouse Platform
Feature Set Not Supported
N/A

8.5
H2O
85%
H2O ranks higher in 2/2 features
H2O ranks higher in 2/2 features
Visualization
N/A
0 Ratings

8.0
80%
1 Rating
Interactive Data Analysis
N/A
0 Ratings

9.0
90%
1 Rating
Data Preparation
Databricks Lakehouse Platform
Feature Set Not Supported
N/A

9.3
H2O
93%
H2O ranks higher in 3/3 features
H2O ranks higher in 3/3 features
Interactive Data Cleaning and Enrichment
N/A
0 Ratings

10.0
100%
1 Rating
Data Transformations
N/A
0 Ratings

9.0
90%
1 Rating
Built-in Processors
N/A
0 Ratings

9.0
90%
1 Rating
Platform Data Modeling
Databricks Lakehouse Platform
Feature Set Not Supported
N/A

10.0
H2O
100%
H2O ranks higher in 4/4 features
H2O ranks higher in 4/4 features
Multiple Model Development Languages and Tools
N/A
0 Ratings

10.0
100%
1 Rating
Automated Machine Learning
N/A
0 Ratings

10.0
100%
1 Rating
Single platform for multiple model development
N/A
0 Ratings

10.0
100%
1 Rating
Self-Service Model Delivery
N/A
0 Ratings

10.0
100%
1 Rating
Model Deployment
Databricks Lakehouse Platform
Feature Set Not Supported
N/A

9.0
H2O
90%
H2O ranks higher in 2/2 features
H2O ranks higher in 2/2 features
Flexible Model Publishing Options
N/A
0 Ratings

10.0
100%
1 Rating
Security, Governance, and Cost Controls
N/A
0 Ratings

8.0
80%
1 Rating
Attribute Ratings
- Databricks Lakehouse Platform (Unified Analytics Platform) is rated higher in 1 area: Likelihood to Recommend
- H2O is rated higher in 1 area: Support Rating
Likelihood to Recommend
8.7
Databricks Lakehouse Platform
87%
15 Ratings

8.1
H2O
81%
3 Ratings
Usability
9.0
Databricks Lakehouse Platform
90%
3 Ratings

H2O
N/A
0 Ratings
Support Rating
7.5
Databricks Lakehouse Platform
75%
2 Ratings

9.0
H2O
90%
2 Ratings
Contract Terms and Pricing Model
8.0
Databricks Lakehouse Platform
80%
1 Rating

H2O
N/A
0 Ratings
Professional Services
10.0
Databricks Lakehouse Platform
100%
1 Rating

H2O
N/A
0 Ratings
Likelihood to Recommend
Databricks Lakehouse Platform
If you need a managed big data megastore, which has native integration with highly optimized Apache Spark Engine and native integration with MLflow, go for Databricks Lakehouse Platform. The Databricks Lakehouse Platform is a breeze to use and analytics capabilities are supported out of the box. You will find it a bit difficult to manage code in notebooks but you will get used to it soon.

Verified User
Engineer in Engineering
Computer Software Company, 1001-5000 employeesH2O
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.

Verified User
Contributor in Engineering
Aviation & Aerospace Company, 10,001+ employeesPros
Databricks Lakehouse Platform
- Process raw data in One Lake (S3) env to relational tables and views
- Share notebooks with our business analysts so that they can use the queries and generate value out of the data
- Try out PySpark and Spark SQL queries on raw data before using them in our Spark jobs
- Modern day ETL operations made easy using Databricks. Provide access mechanism for different set of customers

Verified User
Team Lead in Engineering
Financial Services Company, 10,001+ employeesH2O
- 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
Senior Consultant
A.T. KearneyManagement Consulting, 1001-5000 employees
Cons
Databricks Lakehouse Platform
- Better Localized Testing
- When they were primarily OSS Spark; it was easier to test/manage releases versus the newer DB Runtime. Wish there was more configuration in Runtime less pick a version.
- Graphing Support went non-existent; when it was one of their compelling general engine.

Verified User
Director in Information Technology
Financial Services Company, 201-500 employeesH2O
- Better documentation
- Improve the Visual presentations including charting etc

Verified User
Vice-President in Information Technology
Broadcast Media Company, 51-200 employeesPricing Details
Databricks Lakehouse Platform
General
Free Trial
—Free/Freemium Version
—Premium Consulting/Integration Services
—Entry-level set up fee?
No
Starting Price
$0.07 Per DBU
Databricks Lakehouse Platform Editions & Modules
Edition
Standard | $0.071 |
---|---|
Premium | $0.101 |
Enterprise | $0.131 |
- Per DBU
Additional Pricing Details
—H2O
General
Free Trial
—Free/Freemium Version
—Premium Consulting/Integration Services
—Entry-level set up fee?
No
Starting Price
—H2O Editions & Modules
—
Additional Pricing Details
—Usability
Databricks Lakehouse Platform
Databricks Lakehouse Platform 9.0
Based on 3 answers
Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.
in terms of graph generation and interaction it could improve their UI and UX
in terms of graph generation and interaction it could improve their UI and UX

Verified User
Manager in Product Management
Financial Services Company, 201-500 employeesH2O
No score
No answers yet
No answers on this topic
Support Rating
Databricks Lakehouse Platform
Databricks Lakehouse Platform 7.5
Based on 2 answers
One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.
Director Data Science
CNTransportation/Trucking/Railroad, 10,001+ employees
H2O
H2O 9.0
Based on 2 answers
The overall experience I have with H2O is really awesome, even with its cost effectiveness.

Verified User
Contributor in Engineering
Aviation & Aerospace Company, 10,001+ employeesAlternatives Considered
Databricks Lakehouse Platform
Databricks has a much better edge than Synapse in hundred different ways. Databricks has Photon engine, faster available release in cloud and databricks does not run on Open source spark version so better optimization, better performance and better agility and all kind of performance boost can be achieved in Databricks rather Open source synapse spark

Verified User
Director in Information Technology
Hospitality Company, 10,001+ employeesH2O
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.
Senior Consultant
A.T. KearneyManagement Consulting, 1001-5000 employees
Contract Terms and Pricing Model
Databricks Lakehouse Platform
Databricks Lakehouse Platform 8.0
Based on 1 answer
The problem with this tool and all other ones that are at the top of the industry, it's so expensive that soon as another one will be on the market and deliver the same or different value, it will be catastrophic for them. So you get the fact that they are cashing every dime right now like SAS or Hadoop once did. Now, look at them
Director Data Science
CNTransportation/Trucking/Railroad, 10,001+ employees
H2O
No score
No answers yet
No answers on this topic
Professional Services
Databricks Lakehouse Platform
Databricks Lakehouse Platform 10.0
Based on 1 answer
Again, another level of professional services, this is not their biggest strength but this is the cherry on top. I couldn't think about any other professional services like this one. Now I'm talking about meaningful services that really help out our project and delivery.
Director Data Science
CNTransportation/Trucking/Railroad, 10,001+ employees
H2O
No score
No answers yet
No answers on this topic
Return on Investment
Databricks Lakehouse Platform
- Machine learning is a very new concept and not many universities offer to teach it. My school and a few others have been utilizing Databricks as one of the tools to teach and learn machine learning. By doing this, my university is creating a strong future workforce for the job market.
Freelance Translator
ZOO Digital Group plcEntertainment, 501-1000 employees
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

Verified User
Vice-President in Information Technology
Broadcast Media Company, 51-200 employees