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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
18th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
24
Ranking in other categories
Process Automation (16th), Cloud Data Integration (12th), Integration Platform as a Service (iPaaS) (10th)
Spring Cloud Data Flow
Ranking in Data Integration
21st
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Streaming Analytics (9th)
 

Mindshare comparison

As of June 2025, in the Data Integration category, the mindshare of SnapLogic is 1.4%, down from 1.6% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.2%, 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 solution could improve its API management."
"They are very good at building out new aspects according to customer requirements."
"An important tool for building prototypes and MVPs than can seamlessly turn into production jobs"
"The technical support from SnapLogic is excellent, and I would give it a complete ten."
"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."
"It is a stable solution."
"The initial setup is very straightforward."
"I find the reusability and the snaps to be very valuable features."
"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 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 product is very user-friendly."
"The dashboards in Spring Cloud Dataflow are quite valuable."
"The best thing I like about Spring Cloud Data Flow is its plug-and-play model."
"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 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."
 

Cons

"One area for improvement in SnapLogic is the transparency in the flow of data. It needs to have more transparency. Right now, users only have a preview option at the end of any job flow, so at the end of any Snap Pack, there is a data preview option that lets you review the data and see how it's moving. What would make the solution better is more debugging and more access to change data from the preview panel or more functionality in terms of the preview option."
"The solution isn't ideal for complex processing or logic. We use another solution for that."
"Ultra Pipelines provides real-time ingestion but it needs some adjustment."
"While it performs well, there is some room for improvement in this area."
"SnapLogic sits somewhere in the middle. It doesn’t offer enough easy canned integrations for its users like some of the easier to use integration apps."
"I am looking for more scheduling options. When it comes to scheduling, there are different tools in the market."
"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."
"If the AI capabilities and integrations were more intuitive and easy for new users to learn, it would be greatly beneficial."
"Some of the features, like the monitoring tools, are not very mature and are still evolving."
"I would improve the dashboard features as they are not very user-friendly."
"The solution's community support could be improved."
"Spring Cloud Data Flow is not an easy-to-use tool, so 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."
"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."
"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."
 

Pricing and Cost Advice

"I used the free trial."
"By scaling the solution incrementally the cost is controlled and more beneficial to the client."
"When comparing it with solutions like Apigee or MuleSoft, it still offers better value."
"The cost with SnapLogic is an annual license and better than Informatica."
"It is a higher initial cost than other easy-to-use integration apps."
"The pricing is okay."
"They have pricing/usage tiers that are easy to move up or down."
"SnapLogic is not expensive. It's reasonably priced."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
24%
Manufacturing Company
11%
Computer Software Company
7%
Real Estate/Law Firm
7%
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!
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