We performed a comparison between Amazon MSK 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."The most valuable feature of Amazon MSK is the integration."
"MSK has a private network that's an out-of-box feature."
"It offers good stability."
"It is a stable product."
"Overall, it is very cost-effective based on the workflow."
"Amazon MSK has significantly improved our organization by building seamless integration between systems."
"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."
"The most valuable feature is the Spark cluster which is very fast for heavy loads, big data processing and Pi Spark."
"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."
"The initial setup phase of Databricks was good."
"Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great."
"The built-in optimization recommendations halved the speed of queries and allowed us to reach decision points and deliver insights very quickly."
"The initial setup is pretty easy."
"It's easy to increase performance as required."
"The configuration seems a little complex and the documentation on the product is not available."
"It does not autoscale. Because if you do keep it manually when you add a note to the cluster and then you register it, then it is scalable, but the fact that you have to go and do it, I think, makes it, again, a bit of some operational overhead when managing the cluster."
"It should be more flexible, integration-wise."
"Amazon MSK could improve on the features they offer. They are still lagging behind Confluence."
"It would be really helpful if Amazon MSK could provide a single installation that covers all the servers."
"The product's schema support needs enhancement. It will help enhance integration with many kinds of languages of programming languages, especially for environments using languages like .NET."
"The product should provide more advanced features in future releases."
"The Databricks cluster can be improved."
"The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice."
"Would be helpful to have additional licensing options."
"I have had some issues with some of the Spark clusters running on Databricks, where the Spark runtime and clusters go up and down, which is an area for improvement."
"Doesn't provide a lot of credits or trial options."
"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."
"Implementation of Databricks is still very code heavy."
Amazon MSK is ranked 6th in Streaming Analytics with 6 reviews while Databricks is ranked 2nd in Streaming Analytics with 78 reviews. Amazon MSK is rated 7.2, while Databricks is rated 8.2. The top reviewer of Amazon MSK writes "Efficient real-time transaction tracking but time-consuming installation". On the other hand, the top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". Amazon MSK is most compared with Confluent, Amazon Kinesis, Azure Stream Analytics, Google Cloud Dataflow and Spring Cloud Data Flow, whereas Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and Dremio. See our Amazon MSK vs. Databricks report.
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.