We performed a comparison between SnapLogic and Spring Cloud Data Flow 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."An important tool for building prototypes and MVPs than can seamlessly turn into production jobs"
"SnapLogic is an IPA tool that leverages a low code environment to connect to multiple sources, extract data, and store it in Azure data lake."
"They are very good at building out new aspects according to customer requirements."
"The solution could improve its API management."
"The API architecture makes it easy for orchestration."
"The product is easy to use and has many connectivity options."
"You can use other languages, such as Python, and easily connect to other systems."
"I found SnapLogic valuable and what I found most valuable about it was its ETL feature. I also found its automation feature valuable. It can be used for automating manual activities. It can be used as a middleware for certain transactional data processing and minimal datasets and ETL activities."
"The product is very user-friendly."
"The most valuable feature is real-time streaming."
"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 support is the most important improvement they could make."
"I don't think the support has better knowledge about technologies and tool support. There were lots of times when we had an issue, and it took me quite a long time to explain the problem. I feel like some of the support staff don't know their product well."
"They should expand in terms of features for SaaS-based market requirements in different sectors."
"It needs some more snaps. I would like to see some of the features be changed in some of the snaps."
"The problem is that SnapLogic doesn't offer a wide variety of connectors. For example, integrating with Salesforce is not that easy."
"I am looking for more scheduling options. When it comes to scheduling, there are different tools in the market."
"We'd like there to be more ways for users to get more comfortable and have more experience with the solution to make it easier to use."
"One of the areas for improvement in SnapLogic is that the connectors for some of the applications should be more available in terms of testing in the dev environment. Another area for improvement is that the logging should be standardized, for example, the integration with an ELK stack should be required out-of-the-box, so you can ship the log and have it in the ELK stack. There should be integration with ELK stack for the log shipping."
"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."
"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."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
"Some of the features, like the monitoring tools, are not very mature and are still evolving."
SnapLogic is ranked 14th in Data Integration with 21 reviews while Spring Cloud Data Flow is ranked 28th in Data Integration with 5 reviews. SnapLogic is rated 8.0, while Spring Cloud Data Flow is rated 8.0. The top reviewer of SnapLogic writes "Easy to set up, easy to use, and is low-code". On the other hand, the top reviewer of Spring Cloud Data Flow writes "Provides ease of integration with other cloud platforms ". SnapLogic is most compared with AWS Glue, IBM InfoSphere DataStage, Azure Data Factory, Informatica Cloud Data Integration 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 SnapLogic vs. Spring Cloud Data Flow report.
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