We performed a comparison between JumpMind SymmetricDS and StreamSets based on real PeerSpot user reviews.
Find out what your peers are saying about NetApp, Fivetran, Dell Technologies and others in Data Replication."It is fully featured. It has allowed me to do everything I wanted to do."
"The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customize it to do what you need. Many other tools have started to use features similar to those introduced by StreamSets, like automated workflows that are easy to set up."
"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."
"Also, the intuitive canvas for designing all the streams in the pipeline, along with the simplicity of the entire product are very big pluses for me. The software is very simple and straightforward. That is something that is needed right now."
"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."
"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."
"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 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."
"The most valuable features are the option of integration with a variety of protocols, languages, and origins."
"The user interface could improve. We are looking at some cloud-based databases, and I don't think they support that."
"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 documentation is inadequate and has room for improvement because the technical support does not regularly update their documentation or the knowledge base."
"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."
"StreamSet works great for batch processing but we are looking for something that is more real-time. We need latency in numbers below milliseconds."
"Using ETL pipelines is a bit complicated and requires some technical aid."
"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."
"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."
"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."
JumpMind SymmetricDS is ranked 13th in Data Replication while StreamSets is ranked 8th in Data Integration with 24 reviews. JumpMind SymmetricDS is rated 9.0, while StreamSets is rated 8.4. The top reviewer of JumpMind SymmetricDS writes "Excellent change data capture utility for distributed multi site environment". 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". JumpMind SymmetricDS is most compared with Oracle GoldenGate, AWS Database Migration Service, SSIS, Confluent and Talend Open Studio, whereas StreamSets is most compared with Fivetran, Azure Data Factory, Informatica PowerCenter, SSIS and IBM InfoSphere DataStage.
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