We performed a comparison between Qlik Replicate and StreamSets based on real PeerSpot user reviews.
Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."It's very user-friendly when it comes to settings and configuration. It also offers very detailed logging about warnings and errors."
"The CDC and the flexibility to use QVD as a source are the most valuable features of Qlik Replicate."
"Qlik Replicate stands out with its cutting-edge technology and its ability to handle diverse data management tasks. This powerful tool allows us to efficiently and swiftly load data into various data stores or destinations, while also enabling easy distribution across different endpoints. A notable feature is its capability to reload data from multiple sources by creating multiple tasks within a brief timeframe of fifteen to twenty minutes. This eliminates the need for manual intervention and ensures quick data loading from different tables."
"Support has been great."
"Low-priced reporting and analytics solution, with good scalability and stability. It has on-premises and cloud versions that are cohesive and can integrate well."
"A valuable feature of Qlik Replicate is that you do not need ETL. It's easy to use—you choose two systems and it automatically replicates them. Even if there is no CDC available, if you insert it and update it, and there is nothing to find out, then you can use Qlik Replicate. It's a good product."
"Great with replicating and updating records."
"From a technical perspective, this is an excellent product."
"The most valuable would be the GUI platform that I saw. I first saw it at a special session that StreamSets provided towards the end of the summer. I saw the way you set it up and how you have different processes going on with your data. The design experience seemed to be pretty straightforward to me in terms of how you drag and drop these nodes and connect them with arrows."
"It's very easy to integrate. It integrates with Snowflake, AWS, Google Cloud, and Azure. It's very helpful for DevOps, DataOps, and data engineering because it provides a comprehensive solution, and it's not complicated."
"It is really easy to set up and the interface is easy to use."
"StreamSets data drift feature gives us an alert upfront so we know that the data can be ingested. Whatever the schema or data type changes, it lands automatically into the data lake without any intervention from us, but then that information is crucial to fix for downstream pipelines, which process the data into models, like Tableau and Power BI models. This is actually very useful for us. We are already seeing benefits. Our pipelines used to break when there were data drift changes, then we needed to spend about a week fixing it. Right now, we are saving one to two weeks. Though, it depends on the complexity of the pipeline, we are definitely seeing a lot of time being saved."
"The most valuable feature is the pipelines because they enable us to pull in and push out data from different sources and to manipulate and clean things up within them."
"The scheduling within the data engineering pipeline is very much appreciated, and it has a wide range of connectors for connecting to any data sources like SQL Server, AWS, Azure, etc. We have used it with Kafka, Hadoop, and Azure Data Factory Datasets. Connecting to these systems with StreamSets is very easy."
"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"
"It is a very powerful, modern data analytics solution, in which you can integrate a large volume of data from different sources. It integrates all of the data and you can design, create, and monitor pipelines according to your requirements. It is an all-in-one day data ops solution."
"Support-wise, this solution is in need of improvement."
"In various scenarios, an important consideration is when we encounter issues and Qlik Replicate suggests reloading a specific table. If we face any problems or encounter errors with that table, it becomes necessary to make a change in Qlik Replicate. Performing a full reload every time is not feasible or practical. Instead, we should identify the specific issues and address them without repeating the entire reloading process. Based on this approach, we can investigate and resolve the problem by performing targeted loads from the source itself. This change aligns with my perspective and is something I would like to implement."
"When you remote into it the Qlik Replicate UI a lot of times it just freezes. We set up the EC2, to allow them to go to the server and click on the Replicate icon, it just opens up and just sits there. At that point, we have to go into the EC2 and then reboot the server. This should be fixed, it is frustrating."
"It would be better if the solution’s pricing were more obvious."
"In the next release, I would like to see closer integration with data catalyst."
"We would like to see more details in messages about errors with the system."
"The solution's flexibility to work with APIs should also be improved since it is very weak in working with APIs."
"Support for this product is not great. It needs to be improved."
"One thing that I would like to add is the ability to manually enter data. The way the solution currently works is we don't have the option to manually change the data at any point in time. Being able to do that will allow us to do everything that we want to do with our data. Sometimes, we need to manually manipulate the data to make it more accurate in case our prior bifurcation filters are not good. If we have the option to manually enter the data or make the exact iterations on the data set, that would be a good thing."
"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 monitoring visualization is not that user-friendly. It should include other features to visualize things, like how many records were streamed from a source to a destination on a particular date."
"Sometimes, when we have large amounts of data that is very efficiently stored in Hadoop or Kafka, it is not very efficient to run it through StreamSets, due to the lack of efficiency or the resources that StreamSets is using."
"The data collector in StreamSets has to be designed properly. For example, a simple database configuration with MySQL DB requires the MySQL Connector to be installed."
"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."
"I would like to see it integrate with other kinds of platforms, other than Java. We're going to have a lot of applications using .NET and other languages or frameworks. StreamSets is very helpful for the old Java platform but it's hard to integrate with the other platforms and frameworks."
"We create pipelines or jobs in StreamSets Control Hub. It is a great feature, but if there is a way to have a folder structure or organize the pipelines and jobs in Control Hub, it would be great. I submitted a ticket for this some time back."
Qlik Replicate is ranked 17th in Data Integration with 12 reviews while StreamSets is ranked 8th in Data Integration with 24 reviews. Qlik Replicate is rated 8.2, while StreamSets is rated 8.4. The top reviewer of Qlik Replicate writes "A highly stable solution that can be used to change data capture in legacy systems". 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". Qlik Replicate is most compared with Oracle GoldenGate, AWS Database Migration Service, Qlik Compose, Azure Data Factory and Fivetran, whereas StreamSets is most compared with Fivetran, Azure Data Factory, Informatica PowerCenter, SSIS and IBM InfoSphere DataStage. See our Qlik Replicate vs. StreamSets report.
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