Try our new research platform with insights from 80,000+ expert users

SnapLogic vs Spring Cloud Data Flow comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

SnapLogic
Ranking in Data Integration
21st
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
24
Ranking in other categories
Process Automation (15th), Cloud Data Integration (12th), Integration Platform as a Service (iPaaS) (10th)
Spring Cloud Data Flow
Ranking in Data Integration
24th
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Streaming Analytics (9th)
 

Mindshare comparison

As of April 2025, in the Data Integration category, the mindshare of SnapLogic is 1.5%, up from 1.5% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.1%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

VinethSuresh - PeerSpot reviewer
Achieves rapid results in data migration and has an intuitive user interface
I find SnapLogic to be user-friendly, especially for beginners with limited experience in data engineering or ETL. The interface is interactive, allowing me to quickly learn how to run pipelines and achieve production-ready results swiftly. This agility translates to cost savings, especially for smaller projects and proofs of concept, as less time and effort are needed to deliver results.
NitinGoyal - PeerSpot reviewer
Has a plug-and-play model and provides good robustness and scalability
The solution's community support could be improved. I don't know why the Spring Cloud Data Flow community is not very strong. Community support is very limited whenever you face any problem or are stuck somewhere. I'm not sure whether it has improved in the last six months because this pipeline was set up almost two years ago. I struggled with that a lot. For example, there was limited support whenever I got an exception and sought help from Stack Overflow or different forums. Interacting with Kubernetes needs a few certificates. You need to define all the certificates within your application. With the help of those certificates, your Java application or Spring Cloud Data Flow can interact with Kubernetes. I faced a lot of hurdles while placing those certificates. Despite following the official documentation to define all the replicas, readiness, and liveliness probes within the Spring Cloud Data Flow application, it was not working. So, I had to troubleshoot while digging in and debugging the internals of Spring Cloud Data Flow at that time. It was just a configuration mismatch, and I was doing nothing weird. There was a small spelling difference between how Spring Cloud Data Flow was expecting it and how I passed it. I was just following the official documentation.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The initial setup is very straightforward."
"SnapLogic is more user-friendly than Boomi in terms of debugging. You can move the mouse to a place, and it will record and show the data easily."
"The solution is easy to implement and easy to use. It's basically just drag and drop."
"The connection with SOAP is the best feature."
"The product is easy to use and has many connectivity options."
"The vendor handles the maintenance of the solution"
"The API architecture makes it easy for orchestration."
"By using snaps instead of functions in code, you can see the building blocks of the integration visually. This helps a lot."
"The ease of deployment on Kubernetes, the seamless integration for orchestration of various pipelines, and the visual dashboard that simplifies operations even for non-specialists such as quality analysts."
"The best thing I like about Spring Cloud Data Flow is its plug-and-play model."
"The most valuable feature is real-time streaming."
"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."
"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 solution's most valuable feature is that it allows us to use different batch data sources, retrieve the data, and then do the data processing, after which we can convert and store it in the target."
"The dashboards in Spring Cloud Dataflow are quite valuable."
"The product is very user-friendly."
 

Cons

"SnapLogic should have some inbuilt protocol mechanism in order to speed up."
"There is room for improvement with APM management and how task execution looks."
"The problem is that SnapLogic doesn't offer a wide variety of connectors. For example, integrating with Salesforce is not that easy."
"They should expand in terms of features for SaaS-based market requirements in different sectors."
"While it performs well, there is some room for improvement in this area."
"The dashboards regarding scheduled tasks need further improvement."
"If the AI capabilities and integrations were more intuitive and easy for new users to learn, it would be greatly beneficial."
"What could be improved in SnapLogic is that it was not capable in terms of processing a large number of datasets, but at that point, SnapLogic was evolving. It didn't give a lot of Snaps. I heard recently there are a lot of Snaps getting added and the solution was being enhanced, particularly to connect different data sources. When I was working with SnapLogic six months to one year back, I faced the issue of it not being capable of handling a huge volume of datasets or didn't have much of Snaps, and that was the drawback. If there is any large number of data sets, that's based on or depends on your configuration. If it is a huge volume of data, other traditional ETL tools such as Informatica and Talend can process millions and billions of records, while in SnapLogic, the Snaplex fails or it returns an error in terms of processing that huge volume of data. Informatica, Talend, or any other ETL tool can run for hours in terms of jobs, while SnapLogic jobs fail when the threshold is reached. SnapLogic isn't able to withstand processing, but I don't know if that's still an issue at present, because the solution is getting enhanced and it's been more than six months to one year since I last worked with SnapLogic. There are now a lot of Snaps getting added to the solution, and if it can overcome the limitations I mentioned, SnapLogic could be the go-to tool because currently, it's not being used as much in organizations. It's being used comparatively less compared to other retail tools."
"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."
"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 solution's community support could be improved."
"I would improve the dashboard features as they are not very user-friendly."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
"There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or refreshing the dashboard."
"Spring Cloud Data Flow is not an easy-to-use tool, so improvements are required."
 

Pricing and Cost Advice

"The pricing is okay."
"It is a higher initial cost than other easy-to-use integration apps."
"By scaling the solution incrementally the cost is controlled and more beneficial to the client."
"The license model is based on consumption."
"The cost with SnapLogic is an annual license and better than Informatica."
"SnapLogic's price is high compared to the other tools available in the market."
"I used the free trial."
"From the ROI perspective, the price is extremely high"
"If you want support from Spring Cloud Data Flow there is a fee. The Spring Framework is open-source and this is a free solution."
"This is an open-source product that can be used free of charge."
"The solution provides value for money, and we are currently using its community edition."
report
Use our free recommendation engine to learn which Data Integration solutions are best for your needs.
849,190 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
25%
Manufacturing Company
10%
Computer Software Company
9%
Real Estate/Law Firm
6%
Financial Services Firm
26%
Computer Software Company
17%
Retailer
7%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about SnapLogic?
Despite having no prior experience in SnapLogic, we managed to build, test, and prepare it for release in just three hours, handling heavy data efficiently.
What needs improvement with SnapLogic?
I am quite happy with the solution and do not have specific requirements at the moment. I tend to frequently communicate with SnapLogic to ask for additional features, and they have been responsive...
What is your primary use case for SnapLogic?
I mainly use it for data integration and some API tasks.
What needs improvement with Spring Cloud Data Flow?
There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or r...
What is your primary use case for Spring Cloud Data Flow?
We had a project for content management, which involved multiple applications each handling content ingestion, transformation, enrichment, and storage for different customers independently. We want...
What advice do you have for others considering Spring Cloud Data Flow?
I would definitely recommend Spring Cloud Data Flow. It requires minimal additional effort or time to understand how it works, and even non-specialists can use it effectively with its friendly docu...
 

Also Known As

DataFlow
No data available
 

Overview

 

Sample Customers

Adobe, ADP, BlackBerry, Bonobos, Box, Capital One, Dannon, Eero, Endo, Gensler, HCL, HP, Grovo, HIS, iRobot, Leica, Merck, Sans, Target, Verizon, Vodafone, Yelp, Yahoo!
Information Not Available
Find out what your peers are saying about SnapLogic vs. Spring Cloud Data Flow and other solutions. Updated: April 2025.
849,190 professionals have used our research since 2012.