We performed a comparison between Confluent and StreamSets 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."A person with a good IT background and HTML will not have any trouble with Confluent."
"The most valuable feature of Confluent is the wide range of features provided. They're leading the market in this category."
"The most valuable is its capability to enhance the documentation process, particularly when creating software documentation."
"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."
"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."
"Implementing Confluent's schema registry has significantly enhanced our organization's data quality assurance."
"The documentation process is fast with the tool."
"We mostly use the solution's message queues and event-driven architecture."
"The UI is user-friendly, it doesn't require any technical know-how and we can navigate to social media or use it more easily."
"What I love the most is that StreamSets is very light. It's a containerized application. It's easy to use with Docker. If you are a large organization, it's very easy to use Kubernetes."
"I really appreciate the numerous ready connectors available on both the source and target sides, the support for various media file formats, and the ease of configuring and managing pipelines centrally."
"One of the things I like is the data pipelines. They have a very good design. Implementing pipelines is very straightforward. It doesn't require any technical skill."
"The ability to have a good bifurcation rate and fewer mistakes is valuable."
"The ETL capabilities are very useful for us. We extract and transform data from multiple data sources, into a single, consistent data store, and then we put it in our systems. We typically use it to connect our Apache Kafka with data lakes. That process is smooth and saves us a lot of time in our production systems."
"The Ease of configuration for pipes is amazing. It has a lot of connectors. Mainly, we can do everything with the data in the pipe. I really like the graphical interface too"
"The best feature that I really like is the integration."
"They should remove Zookeeper because of security issues."
"It could be improved by including a feature that automatically creates a new topic and puts failed messages."
"Confluent has a good monitoring tool, but it's not customizable."
"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."
"It would help if the knowledge based documents in the support portal could be available for public use as well."
"Areas for improvement include implementing multi-storage support to differentiate between database stores based on data age and optimizing storage costs."
"Confluent's price needs improvement."
"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."
"We've seen a couple of cases where it appears to have a memory leak or a similar problem."
"There aren't enough hands-on labs, and debugging is also an issue because it takes a lot of time. Logs are not that clear when you are debugging, and you can only select a single source for a pipeline."
"StreamSets should provide a mechanism to be able to perform data quality assessment when the data is being moved from one source to the target."
"The software is very good overall. Areas for improvement are the error logging and the version history. I would like to see better, more detailed error logging information."
"The execution engine could be improved. When I was at their session, they were using some obscure platform to run. There is a controller, which controls what happens on that, but you should be able to easily do this at any of the cloud services, such as Google Cloud. You shouldn't have any issues in terms of how to run it with their online development platform or design platform, basically their execution engine. There are issues with that."
"They need to improve their customer care services. Sometimes it has taken more than 48 hours to resolve an issue. That should be reduced. They are aware of small or generic issues, but not the more technical or deep issues. For those, they require some time, generally 48 to 72 hours to respond. That should be improved."
"I would like to see further improvement in the UI. In addition, upgrades are not automatic and they should be automated. Currently, we have to manually upgrade versions."
"The logging mechanism could be improved. If I am working on a pipeline, then create a job out of it and it is running, it will generate constant logs. So, the logging mechanism could be simplified. Now, it is a bit difficult to understand and filter the logs. It takes some time."
Confluent is ranked 4th in Streaming Analytics with 19 reviews while StreamSets is ranked 8th in Data Integration with 24 reviews. Confluent is rated 8.4, while StreamSets is rated 8.4. 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 StreamSets writes "We no longer need to hire highly skilled data engineers to create and monitor data pipelines". Confluent is most compared with Amazon MSK, Amazon Kinesis, Databricks, AWS Glue and Oracle GoldenGate, whereas StreamSets is most compared with Fivetran, Azure Data Factory, Informatica PowerCenter, SSIS and SnapLogic. See our Confluent vs. StreamSets report.
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.
