We performed a comparison between Spring Cloud Data Flow and StreamSets based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration."The most valuable feature is real-time streaming."
"The product is very user-friendly."
"There are a lot of options in Spring Cloud. It's flexible in terms of how we can use it. It's a full infrastructure."
"The most valuable features of Spring Cloud Data Flow are the simple programming model, integration, dependency Injection, and ability to do any injection. Additionally, auto-configuration is another important feature because we don't have to configure the database and or set up the boilerplate in the database in every project. The composability is good, we can create small workloads and compose them in any way we like."
"The best feature that I really like is the integration."
"The ability to have a good bifurcation rate and fewer mistakes is valuable."
"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."
"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 entire user interface is very simple and the simplicity of creating pipelines is something that I like very much about it. The design experience is very smooth."
"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."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
"Spring Cloud Data Flow could improve the user interface. We can drag and drop in the application for the configuration and settings, and deploy it right from the UI, without having to run a CI/CD pipeline. However, that does not work with Kubernetes, it only works when we are working with jars as the Spring Cloud Data Flow applications."
"Some of the features, like the monitoring tools, are not very mature and are still evolving."
"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."
"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."
"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."
"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."
"We often faced problems, especially with SAP ERP. We struggled because many columns weren't integers or primary keys, which StreamSets couldn't handle. We had to restructure our data tables, which was painful. Also, pipeline failures were common, and data drifting wasn't addressed, which made things worse. Licensing was another issue we encountered."
"StreamSet works great for batch processing but we are looking for something that is more real-time. We need latency in numbers below milliseconds."
"If you use JDBC Lookup, for example, it generally takes a long time to process data."
"Visualization and monitoring need to be improved and refined."
Spring Cloud Data Flow is ranked 29th in Data Integration with 5 reviews while StreamSets is ranked 8th in Data Integration with 24 reviews. Spring Cloud Data Flow is rated 8.0, while StreamSets is rated 8.4. The top reviewer of Spring Cloud Data Flow writes "Provides ease of integration with other cloud platforms ". 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". Spring Cloud Data Flow is most compared with Apache Flink, Google Cloud Dataflow, Apache Spark Streaming, Azure Data Factory and Oracle Data Integrator (ODI), whereas StreamSets is most compared with Fivetran, Azure Data Factory, Informatica PowerCenter, SSIS and AWS Database Migration Service.
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