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."
"I find Confluent's Kafka Connectors and Kafka Streams invaluable for my use cases because they simplify real-time data processing and ETL tasks by providing reliable, pre-packaged connectors and tools."
"It is also good for knowledge base management."
"The most valuable feature of Confluent is the wide range of features provided. They're leading the market in this category."
"A person with a good IT background and HTML will not have any trouble with Confluent."
"I would rate the scalability of the solution at eight out of ten. We have 20 people who use Confluent in our organization now, and we hope to increase usage in the future."
"The most valuable feature that we are using is the data replication between the data centers allowing us to configure a disaster recovery or software. However, is it's not mandatory to use and because most of the features that we use are from Apache Kafka, such as end-to-end encryption. Internally, we can develop our own kind of product or service from Apache Kafka."
"Implementing Confluent's schema registry has significantly enhanced our organization's data quality assurance."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"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."
"One of the features provides nice interactive clusters, or compute instances that you don't really need to manage often."
"Automation with Databricks is very easy when using the API."
"Databricks has a scalable Spark cluster creation process. The creators of Databricks are also the creators of Spark, and they are the industry leaders in terms of performance."
"I haven't heard about any major stability issues. At this time I feel like it's stable."
"It is fast, it's scalable, and it does the job it needs to do."
"The initial setup phase of Databricks was good."
"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."
"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."
"The formatting aspect within the page can be improved and more powerful."
"Confluence could improve the server version of the solution. However, most companies are going to the cloud."
"They should remove Zookeeper because of security issues."
"The pricing model should include the ability to pick features and be charged for them only."
"It could be more user-friendly and centralized. A way to reduce redundancy would be helpful."
"It requires some application specific connectors which are lacking. This needs to be added."
"In the future, I would like to see Data Lake support. That is something that I'm looking forward to."
"The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice."
"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."
"It would be great if Databricks could integrate all the cloud platforms."
"Databricks would benefit from enhanced metrics and tighter integration with Azure's diagnostics."
"Databricks requires writing code in Python or SQL, so if you're a good programmer then you can use Databricks."
"The integration features could be more interesting, more involved."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
Confluent is ranked 4th in Streaming Analytics with 21 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 Dremio. See our Confluent vs. Databricks report.
See our list of best Streaming Analytics vendors.
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