We performed a comparison between Databricks and Domo based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The solution is very easy to use."
"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."
"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 ability to stream data and the windowing feature are valuable."
"The simplicity of development is the most valuable feature."
"The most valuable feature of Databricks is the integration of the data warehouse and data lake, and the development of the lake house. Additionally, it integrates well with Spark for processing data in production."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"We are completely satisfied with the ease of connecting to different sources of data or pocket files in the search"
"The user interface is quite good."
"Domo is not a difficult tool to learn. All you need to know is the SQL for the ETL part. You don't need to write much code. That's the great part. It uses legacy languages, like SQL, which is very common among developers who then don't have to go and learn Domo's own syntax. Therefore, you don't have to learn another hard language to use Domo."
"The fact that you can add any data source is valuable. The entire data handling suite they have, all the apps, etc., is pretty amazing. One of the key things, not being a techie or a data-warehouse guy, is that you can connect data sources, and do all kinds of pretty amazing things."
"The ETL tools they have in Redshift are pretty awesome... I can work in Redshift to get the data from AWS and work in Redshift, in Domo, to create Transforms and the data structure we need..."
"The best thing is that the data storage is pretty much free. I can store as much data as I want, from different sources."
"The dashboard is the most valuable feature and allows for customization to create and share reports."
"I mostly see it as an ETL which has many system connectors. It does a good job of ETL."
"In Workbench 5, they have come up with a very useful feature called Upsert. When you're pushing data into the data set, if the data is already available it will update the data, and if that the data is not there it will insert it. That is a beneficial feature that they introduced in the latest version."
"The solution has some scalability and integration limitations when consolidating legacy systems."
"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."
"It would be great if Databricks could integrate all the cloud platforms."
"Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with."
"In the next release, I would like to see more optimization features."
"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good."
"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."
"Support for Microsoft technology and the compatibility with the .NET framework is somewhat missing."
"It is expensive."
"Their STK is not up to date and you can't access it on their website. They have a private STK to access resources in Domo."
"It's quite slow. We are using about 2,000,000 rows of data. Creating certain reports takes almost a couple of minutes, which should not be the case."
"There were very few cases on some of the tables, the data tables, where I wish there was an additional feature or two."
"It is expensive."
"The preconfigured apps need to be more relevant to allow one, out of the box, to load data in order to use pre-set reports/views."
"There's a learning curve before you can get used to the solution."
"When you're exporting a graph out of Domo — suppose it is in the form of a donut chart or it is in form of a stack — the data comes out in tabular format, not as a graph. When exporting the data, I would like them to create a tab for graphs and another tab with the data in tabular format."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Domo is ranked 11th in BI (Business Intelligence) Tools with 35 reviews. Databricks is rated 8.2, while Domo is rated 7.8. The top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". On the other hand, the top reviewer of Domo writes "Robust, powerful, and easy to use". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Dremio and Microsoft Azure Machine Learning Studio, whereas Domo is most compared with Tableau, Microsoft Power BI, Looker, Amazon QuickSight and Apache Superset. See our Databricks vs. Domo report.
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