We performed a comparison between Confluent 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 design of the product is extremely well built and it is highly configurable."
"Their tech support is amazing; they are very good, both on and off-site."
"Kafka Connect framework is valuable for connecting to the various source systems where code doesn't need to be written."
"Implementing Confluent's schema registry has significantly enhanced our organization's data quality assurance."
"The most valuable is its capability to enhance the documentation process, particularly when creating software documentation."
"The solution can handle a high volume of data because it works and scales well."
"The monitoring module is impressive."
"The most valuable feature of Confluent is the wide range of features provided. They're leading the market in this category."
"The solution is very easy to use."
"The Delta Lake data type has been the most useful part of this solution. Delta Lake is an opensource data type and it was implemented and invented by Databricks."
"It's great technology."
"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."
"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."
"We have the ability to scale, collaborate and do machine learning."
"The load distribution capabilities are good, and you can perform data processing tasks very quickly."
"It can send out large data amounts."
"In Confluent, there could be a few more VPN options."
"Currently, in the early stages, I see a gap on the security side. If you are using the SaaS version, we would like to get a fuller, more secure solution that can be adopted right out of the box. Confluence could do a better job sharing best practices or a reusable pattern that others have used, especially for companies that can not afford to hire professional services from Confluent."
"there is room for improvement in the visualization."
"The Schema Registry service could be improved. I would like a bigger knowledge base of other use cases and more technical forums. It would be good to have more flexible monitoring features added to the next release as well."
"There is no local support team in Saudi Arabia."
"It could have more themes. They should also have more reporting-oriented plugins as well. It would be great to have free custom reports that can be dispatched directly from Jira."
"There is a limitation when it comes to seamlessly importing Microsoft documents into Confluent pages, which can be inconvenient for users who frequently work with Microsoft Office tools and need to transition their content to Confluent."
"The product should integrate tools for incorporating diagrams like Lucidchart. It also needs to improve its formatting features. We also faced issues while granting permissions."
"There should be better integration with other platforms."
"We'd like a more visual dashboard for analysis It needs better UI."
"Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists."
"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."
"I would like it if Databricks made it easier to set up a project."
"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."
"The solution has some scalability and integration limitations when consolidating legacy systems."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
Confluent is ranked 4th in Streaming Analytics with 20 reviews while Databricks is ranked 2nd in Streaming Analytics with 78 reviews. Confluent is rated 8.4, while Databricks is rated 8.2. The top reviewer of Confluent writes "Has good technical support services and a valuable feature for real-time data streaming ". On the other hand, the top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". Confluent is most compared with Amazon MSK, Amazon Kinesis, AWS Glue, Oracle GoldenGate and Fivetran, whereas Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku and Microsoft Azure Machine Learning Studio. See our Confluent vs. Databricks report.
See our list of best Streaming Analytics vendors.
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