We performed a comparison between Matillion ETL and Spring Cloud Data Flow based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Matillion ETL has great Git integration that is perfect and convenient to use."
"Matillion ETL helps manage data movement, ingestion, and transformation through pipelines."
"It can scale to a great extent. It can handle the load that we are putting on it, which is about 5TBs."
"It takes less than five minutes to set up and delivers results. It is much quicker than traditional ETL technologies."
"The product's initial setup phase was easy."
"It is pretty user-friendly, even for people who aren't super technical."
"It has good integrations with Amazon Redshift and other AWS services."
"The technical support treats us well. They already have a support portal, and they are responsive, which helps."
"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 product is very user-friendly."
"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 most valuable feature is real-time streaming."
"The improvement area could be possible if the tool provides better integration capabilities with other ecosystems, including governance tools or data cataloging tools, as it is currently an area where the solution is lacking."
"The current version is a bit more limited because it's on a virtual machine, and everything executes on that one virtual machine."
"Going forward, I would like them to add custom jobs, since we still have to run these outside of Matillion."
"The tool's lineage is very weak."
"Unlike Snowflake which automatically takes care of upgrading to the latest version and includes additional features, with Matillion ETL we need to do this ourselves."
"Matillion’s on-premises capabilities don’t allow you to build something customized."
"Our main challenge currently is that Matillion runs on an EC2 instance, limiting us to running only two processes simultaneously at the entry level."
"Ideally, I would like it to integrate with Secrets Manager as well as the AWS."
"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."
"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."
Matillion ETL is ranked 4th in Cloud Data Integration with 24 reviews while Spring Cloud Data Flow is ranked 29th in Data Integration with 5 reviews. Matillion ETL is rated 8.6, while Spring Cloud Data Flow is rated 8.0. The top reviewer of Matillion ETL writes "Efficient data integration and transformation with seamless cloud-native integration". On the other hand, the top reviewer of Spring Cloud Data Flow writes "Provides ease of integration with other cloud platforms ". Matillion ETL is most compared with Snowflake, Azure Data Factory, AWS Glue, Informatica PowerCenter and SSIS, whereas Spring Cloud Data Flow is most compared with Apache Flink, Google Cloud Dataflow, Apache Spark Streaming, Azure Data Factory and TIBCO BusinessWorks. See our Matillion ETL vs. Spring Cloud Data Flow report.
We monitor all Cloud Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
