We performed a comparison between Alteryx and Databricks based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Databricks has a slight edge in this comparison. It received better marks in the pricing category than Alteryx did.
"The drag-and-drop features are useful for data scientists who do not like to code because it is already in the system."
"My primary focus is creating numerous data pulls, and Alteryx Server handles the automation well."
"I like that I can merge data from different sources into one place."
"Alteryx's connectivity is essential. We like the ability to connect the solution to multiple sources. It's easier than other data modeling and extraction solutions. It's built on a self-service concept, so it's easy for anyone to open the tool and directly import or export data from it."
"Technical support is very helpful."
"Alteryx has made us more agile and increased the speed and effectiveness of decision making."
"Geo features have made spatial mapping large retail universes possible."
"The three data signs and data engineering are great features."
"It is a cost-effective solution."
"The solution is an impressive tool for data migration and integration."
"The processing capacity is tremendous in the database."
"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 aspect of the solution is its notebook. It's quite convenient to use, both terms of the research and the development and also the final deployment, I can just declare the spark jobs by the load tables. It's quite convenient."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"The solution is very simple and stable."
"Databricks has helped us have a good presence in data."
"Even when it already includes some AI models, this area could be improved."
"I honestly can't think of anything that needs to be improved."
"In the database, it should be more functional and connect to more big data, especially using IPI."
"There could be a bit of improvement related to performance. Sometimes it demands a lot of resources for running it, like memory and search."
"The solution can be made more affordable."
"A colleague of mind mentioned that the solution should have more options for the visualization of data."
"The server is too expensive for what you get and it really a designer desktop on a server."
"They should work on its pricing."
"Databricks has a lack of debuggers, and it would be good to see more components."
"Implementation of Databricks is still very code heavy."
"Can be improved by including drag-and-drop features."
"I would like to see more documentation in terms of how an end-user could use it, and users like me can easily try it and implement use cases."
"The connectivity with various BI tools could be improved, specifically the performance and real time integration."
"Databricks would benefit from enhanced metrics and tighter integration with Azure's diagnostics."
"I would like to see the integration between Databricks and MLflow improved. It is quite hard to train multiple models in parallel in the distributed fashions. You hit rate limits on the clients very fast."
"CI/CD needs additional leverage and support."
Alteryx is ranked 3rd in Data Science Platforms with 74 reviews while Databricks is ranked 1st in Data Science Platforms with 78 reviews. Alteryx is rated 8.4, while Databricks is rated 8.2. The top reviewer of Alteryx writes "Feature-rich ETL that condenses a number of functions into one tool". On the other hand, the top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". Alteryx is most compared with KNIME, Dataiku, RapidMiner, Tableau and Microsoft Power BI, whereas Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Dremio and Apache Flink. See our Alteryx vs. Databricks report.
See our list of best Data Science Platforms vendors.
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.