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."We use Qlik Replicate to change data capture of databases in production environments."
"It enables us to transform data at the latest stage rather than in ETL loads, so it's more ELT which is one of the advantages. It is also in near real-time, which brings significant advantage for our embedded analytics approach."
"Support has been great."
"Great with replicating and updating records."
"The CDC and the flexibility to use QVD as a source are the most valuable features of Qlik Replicate."
"A pretty good series of connectors is one of the best features of Qlik Replicate."
"It's very user-friendly when it comes to settings and configuration. It also offers very detailed logging about warnings and errors."
"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."
"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."
"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."
"StreamSets’ data drift resilience has reduced the time it takes us to fix data drift breakages. For example, in our previous Hadoop scenario, when we were creating the Sqoop-based processes to move data from source to destinations, we were getting the job done. That took approximately an hour to an hour and a half when we did it with Hadoop. However, with the StreamSets, since it works on a data collector-based mechanism, it completes the same process in 15 minutes of time. Therefore, it has saved us around 45 minutes per data pipeline or table that we migrate. Thus, it reduced the data transfer, including the drift part, by 45 minutes."
"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"
"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."
"Important features include that it comprises lots of functionality to connect data from various sources through connector availability, scheduling pipelines at any time, and integration with third-party and security solutions for encryption."
"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."
"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."
"In the next release, I would like to see closer integration with data catalyst."
"It's not possible to replicate the QVC files in data analytics."
"The solution's flexibility to work with APIs should also be improved since it is very weak in working with APIs."
"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."
"This product could be improved by providing more insight regarding errors. One of our customers that uses Qlik Replicate has had an issue. We tried to debug it, but we could not trace the error message. The infrastructure site should give us more insight about errors. Qlik Replicate is not a business solution, it's an IT solution. The reporting tools and bug site should be improved."
"We'd like better connectivity."
"It would be better if the solution’s pricing were more obvious."
"The UI and data version control can be improved."
"The documentation is inadequate and has room for improvement because the technical support does not regularly update their documentation or the knowledge base."
"In terms of the product, I don't think there is any room for improvement because it is very good. One small area of improvement that is very much needed is on the knowledge base side. Sometimes, it is not very clear how to set up a certain process or a certain node for a person who's using the platform for the first time."
"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."
"One area for improvement could be the cloud storage server speed, as we have faced some latency issues here and there."
"Visualization and monitoring need to be improved and refined."
"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."
"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."
"Currently, we can only use the query to read data from SAP HANA. What we would like to see, as soon as possible, is the ability to read from multiple tables from SAP HANA. That would be a really good thing that we could use immediately. For example, if you have 100 tables in SQL Server or Oracle, then you could just point it to the schema or the 100 tables and ingestion information. However, you can't do that in SAP HANA since StreamSets currently is lacking in this. They do not have a multi-table feature for SAP HANA. Therefore, a multi-table origin for SAP HANA would be helpful."
Qlik Replicate is ranked 16th in Data Integration with 12 reviews while StreamSets is ranked 8th in Data Integration with 23 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 Oracle GoldenGate. See our Qlik Replicate vs. StreamSets report.
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