We performed a comparison between Cloudera DataFlow and Databricks based on real PeerSpot user reviews.
Find out in this report how the two Streaming Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."This solution is very scalable and robust."
"DataFlow's performance is okay."
"The initial setup was not so difficult"
"The most effective features are data management and analytics."
"I like how easy it is to share your notebook with others. You can give people permission to read or edit. I think that's a great feature. You can also pull in code from GitHub pretty easily. I didn't use it that often, but I think that's a cool feature."
"Databricks is a unified solution that we can use for streaming. It is supporting open source languages, which are cloud-agnostic. When I do database coding if any other tool has a similar language pack to Excel or SQL, I can use the same knowledge, limiting the need to learn new things. It supports a lot of Python libraries where I can use some very easily."
"The fast data loading process and data storage capabilities are great."
"Databricks has improved my organization by allowing us to transform data from sources to a different format and feed that to the analytics, business intelligence, and reporting teams. This tool makes it easy to do those kinds of things."
"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."
"We are completely satisfied with the ease of connecting to different sources of data or pocket files in the search"
"I haven't heard about any major stability issues. At this time I feel like it's stable."
"The most valuable feature is the Spark cluster which is very fast for heavy loads, big data processing and Pi Spark."
"It is not easy to use the R language. Though I don't know if it's possible, I believe it is possible, but it is not the best language for machine learning."
"It's an outdated legacy product that doesn't meet the needs of modern data analysts and scientists."
"Although their workflow is pretty neat, it still requires a lot of transformation coding; especially when it comes to Python and other demanding programming languages."
"The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice."
"Databricks has a lack of debuggers, and it would be good to see more components."
"The initial setup is difficult."
"There would also be benefits if more options were available for workers, or the clusters of the two points."
"There should be better integration with other platforms."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."
"There is room for improvement in visualization."
Cloudera DataFlow is ranked 13th in Streaming Analytics with 4 reviews while Databricks is ranked 2nd in Streaming Analytics with 78 reviews. Cloudera DataFlow is rated 7.2, while Databricks is rated 8.2. The top reviewer of Cloudera DataFlow writes "Has good data management and analytics features". On the other hand, the top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". Cloudera DataFlow is most compared with Confluent, Amazon MSK, Informatica Data Engineering Streaming, Hortonworks Data Platform and Spring Cloud Data Flow, whereas Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Dremio and Microsoft Azure Machine Learning Studio. See our Cloudera DataFlow vs. Databricks report.
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