We performed a comparison between Collibra Catalog and StreamSets based on real PeerSpot user reviews.
Find out what your peers are saying about Informatica, Alation, Collibra and others in Metadata Management."Collibra Catalog's best feature is the data quality checker."
"The data lineage capability is valuable as it shows how different sources are connected and how data flows, which is crucial for projects like migrations. Moreover, data lineage visualization in Collibra Catalog aids our data governance initiatives."
"Collibra Catalog is simple to use and user-friendly for those who are not technically inclined since it is easy to find while also easy to see data lineage diagrams."
"Collibra Catalog has significantly enhanced data governance and compliance for our team, primarily through its valuable feature of endpoint lineage enabling visual representation of the data."
"We have had no complaints about the stability."
"The most valuable features are the option of integration with a variety of protocols, languages, and origins."
"It is really easy to set up and the interface is easy to use."
"For me, the most valuable features in StreamSets have to be the Data Collector and Control Hub, but especially the Data Collector. That feature is very elegant and seamlessly works with numerous source 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."
"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."
"StreamSets Transformer is a good feature because it helps you when you are developing applications and when you don't want to write a lot of code. That is the best feature overall."
"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."
"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."
"I'd like to see more integration with other reporting sources."
"A key area for improvement in Collibra Catalog lies in its integration capabilities, particularly with a broader range of sources."
"Collibra Catalog could improve its automation to increase the efficiency of the software."
"The tool's overall functionalities need to improve since, nowadays, many tools, from a business perspective, are easy to use."
"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 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."
"StreamSet works great for batch processing but we are looking for something that is more real-time. We need latency in numbers below milliseconds."
"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."
"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."
"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 documentation is inadequate and has room for improvement because the technical support does not regularly update their documentation or the knowledge base."
"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."
Collibra Catalog is ranked 3rd in Metadata Management with 5 reviews while StreamSets is ranked 8th in Data Integration with 24 reviews. Collibra Catalog is rated 7.8, while StreamSets is rated 8.4. The top reviewer of Collibra Catalog writes "A user-friendly for those who are not technically inclined and useful for cataloging various reports". 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". Collibra Catalog is most compared with Informatica Enterprise Data Catalog, Ab Initio Co>Operating System, Talend Data Management Platform, Palantir Foundry and Denodo, whereas StreamSets is most compared with Fivetran, Azure Data Factory, Informatica PowerCenter, SSIS and IBM InfoSphere DataStage.
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