We performed a comparison between Databricks and Dell Streaming Data Platform based on real PeerSpot user reviews.
Find out what your peers are saying about Amazon Web Services (AWS), Databricks, Microsoft and others in Streaming Analytics."The load distribution capabilities are good, and you can perform data processing tasks very quickly."
"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."
"It's very simple to use Databricks Apache Spark."
"The solution is very simple and stable."
"I haven't heard about any major stability issues. At this time I feel like it's stable."
"The processing capacity is tremendous in the database."
"I like that Databricks is a unified platform that lets you do streaming and batch processing in the same place. You can do analytics, too. They have added something called Databricks SQL Analytics, allowing users to connect to the data lake to perform analytics. Databricks also will enable you to share your data securely. It integrates with your reporting system as well."
"The ability to stream data and the windowing feature are valuable."
"The performance and price is good."
"The integration of data could be a bit better."
"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."
"A lot of people are required to manage this solution."
"It's not easy to use, and they need a better UI."
"Databricks' technical support takes a while to respond and could be improved."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"It would be nice to have more guidance on integrations with ETLs and other data quality tools."
"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."
"Improvement can be made by implementing a clear sales point that guides users in making choices, especially for virtualization purposes."
Databricks is ranked 2nd in Streaming Analytics with 78 reviews while Dell Streaming Data Platform is ranked 16th in Streaming Analytics with 1 review. Databricks is rated 8.2, while Dell Streaming Data Platform is rated 8.0. 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 Dell Streaming Data Platform writes "The solution’s clear-cut pricing makes scalability a cinch". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Microsoft Azure Machine Learning Studio and Dremio, whereas Dell Streaming Data Platform is most compared with Confluent.
See our list of best Streaming Analytics vendors.
We monitor all Streaming Analytics 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.