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Databricks vs H2O.ai comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Databricks
Ranking in Data Science Platforms
1st
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
88
Ranking in other categories
Cloud Data Warehouse (7th), Streaming Analytics (1st)
H2O.ai
Ranking in Data Science Platforms
20th
Average Rating
7.6
Reviews Sentiment
7.2
Number of Reviews
8
Ranking in other categories
Model Monitoring (6th)
 

Mindshare comparison

As of April 2025, in the Data Science Platforms category, the mindshare of Databricks is 18.2%, down from 19.1% compared to the previous year. The mindshare of H2O.ai is 1.5%, up from 1.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

ShubhamSharma7 - PeerSpot reviewer
Capability to integrate diverse coding languages in a single notebook greatly enhances workflow
Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.
Kashif Yaseen - PeerSpot reviewer
Plug-and-play convenience enhances productivity but needs better multimodal support
We mostly used the solution in the domain that I'm working. We had most of the use cases around chatbots and conversational BI The solution was plug-and-play, meaning most of the components were handled by the solution itself rather than building them from scratch. This was useful for our banking…

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"It's very simple to use Databricks Apache Spark."
"Ability to work collaboratively without having to worry about the infrastructure."
"Databricks has a scalable Spark cluster creation process. The creators of Databricks are also the creators of Spark, and they are the industry leaders in terms of performance."
"The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes."
"The initial setup is pretty easy."
"What I like about Databricks is that it's one of the most popular platforms that give access to folks who are trying not just to do exploratory work on the data but also go ahead and build advanced modeling and machine learning on top of that."
"Databricks helps crunch petabytes of data in a very short period of time."
"The most valuable feature of H2O.ai is that it is plug-and-play."
"One of the most interesting features of the product is their driverless component. The driverless component allows you to test several different algorithms along with navigating you through choosing the best algorithm."
"The ease of use in connecting to our cluster machines."
"It is helpful, intuitive, and easy to use. The learning curve is not too steep."
"AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."
"The most valuable features are the machine learning tools, the support for Jupyter Notebooks, and the collaboration that allows you to share it across people."
"Fast training, memory-efficient DataFrame manipulation, well-documented, easy-to-use algorithms, ability to integrate with enterprise Java apps (through POJO/MOJO) are the main reasons why we switched from Spark to H2O."
 

Cons

"We'd like a more visual dashboard for analysis It needs better UI."
"There could be more support for automated machine learning in the database. I would like to see more ways to do analysis so that the reporting is more understandable."
"In the next release, I would like to see more optimization features."
"The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice."
"Instead of relying on a massive instance, the solution should offer micro partition levels. They're working on it, however, they need to implement it to help the solution run more effectively."
"While Databricks is generally a robust solution, I have noticed a limitation with debugging in the Delta Live Table, which could be improved."
"I would like it if Databricks adopted an interface more like R Studio. When I create a data frame or a table, R Studio provides a preview of the data. In R Studio, I can see that it created a table with so many columns or rows. Then I can click on it and open a preview of that data."
"The solution could be improved by adding a feature that would make it more user-friendly for our team. The feature is simple, but it would be useful. Currently, our team is more familiar with the language R, but Databricks requires the use of Jupyter Notebooks which primarily supports Python. We have tried using RStudio, but it is not a fully integrated solution. To fully utilize Databricks, we have to use the Jupyter interface. One feature that would make it easier for our team to adopt the Jupyter interface would be the ability to select a specific variable or line of code and execute it within a cell. This feature is available in other Jupyter Notebooks outside of Databricks and in our own IDE, but it is not currently available within Databricks. If this feature were added, it would make the transition to using Databricks much smoother for our team."
"Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive."
"It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O."
"H2O.ai can improve in areas like multimodal support and prompt engineering."
"The model management features could be improved."
"On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time."
"The interpretability module has room for improvement. Also, it needs to improve its ability to integrate with other systems, like SageMaker, and the overall integration capability."
"I would like to see more features related to deployment."
"It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."
 

Pricing and Cost Advice

"The solution is affordable."
"Price-wise, I would rate Databricks a three out of five."
"The basic version of this solution is now open-source, so there are no license costs involved. However, there is a charge for any advanced functionality and this can be quite expensive."
"The solution requires a subscription."
"I rate the price of Databricks as eight out of ten."
"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."
"We have only incurred the cost of our AWS cloud services. This is because during this period, Databricks provided us with an extended evaluation period, and we have not spent much money yet. We are just starting to incur costs this month, I will know more later on the full cost perspective."
"It is an expensive tool. The licensing model is a pay-as-you-go one."
"We have seen significant ROI where we were able to use the product in certain key projects and could automate a lot of processes. We were even able to reduce staff."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
11%
Manufacturing Company
9%
Healthcare Company
6%
Financial Services Firm
18%
Computer Software Company
12%
Manufacturing Company
8%
Energy/Utilities Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

Which do you prefer - Databricks or Azure Machine Learning Studio?
Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...
How would you compare Databricks vs Amazon SageMaker?
We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...
Which would you choose - Databricks or Azure Stream Analytics?
Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...
What needs improvement with H2O.ai?
H2O.ai can improve in areas like multimodal support and prompt engineering. They are already working on updates and changes. Although I haven't explored all the new products they've added to their ...
What is your primary use case for H2O.ai?
We mostly used the solution in the domain that I'm working. We had most of the use cases around chatbots and conversational BI.
What advice do you have for others considering H2O.ai?
It is important to address data privacy concerns and ensure you're choosing the right vendor that meets your use case demands. Also, you may leave my name, Kashif, but please keep the company name ...
 

Comparisons

 

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
No data available
 

Overview

 

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
Find out what your peers are saying about Databricks vs. H2O.ai and other solutions. Updated: April 2025.
849,190 professionals have used our research since 2012.