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SnapLogic vs Spring Cloud Data Flow comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

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

Customer Service

Sentiment score
8.5
SnapLogic's customer service is seen as responsive by some, but others report delays and insufficient support knowledge.
No sentiment score available
 

Room For Improvement

Sentiment score
6.2
SnapLogic needs improvements in complex processing, data flow transparency, API monitoring, user dashboards, support, debugging, and high-volume data handling.
No sentiment score available
 

Scalability Issues

Sentiment score
8.0
SnapLogic is praised for cloud scalability, user-friendly setup, and flexible resource allocation, though some face initial setup challenges.
No sentiment score available
 

Setup Cost

Sentiment score
6.5
SnapLogic offers reasonable, consumption-based pricing that remains affordable despite recent increases, especially compared to competitors.
No sentiment score available
 

Stability Issues

Sentiment score
7.5
SnapLogic is generally stable with minimal bugs and downtime, though some users experience availability issues and job failures with large data.
No sentiment score available
 

Valuable Features

Sentiment score
8.8
SnapLogic provides an intuitive, hybrid deployment platform with low-code development, seamless app integration, high data transfer, and extensive API management.
No sentiment score available
 

Categories and Ranking

SnapLogic
Ranking in Data Integration
24th
Average Rating
7.8
Reviews Sentiment
7.7
Number of Reviews
22
Ranking in other categories
Process Automation (16th), Cloud Data Integration (13th), Integration Platform as a Service (iPaaS) (10th)
Spring Cloud Data Flow
Ranking in Data Integration
22nd
Average Rating
7.8
Reviews Sentiment
6.7
Number of Reviews
9
Ranking in other categories
Streaming Analytics (10th)
 

Featured Reviews

Selva Dhoom - PeerSpot reviewer
Automates manual activities and has helpful documentation that allows users to self-study
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.
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.
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Top Industries

By visitors reading reviews
Financial Services Firm
25%
Manufacturing Company
11%
Computer Software Company
9%
Real Estate/Law Firm
5%
Financial Services Firm
29%
Computer Software Company
17%
Manufacturing Company
7%
Retailer
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?
The biggest issue we have faced in our company with SnapLogic is regarding the EDI format. For instance, suppose if 20 EDIs are shortlisted then SnapLogic will convert and provide only those specif...
What is your primary use case for SnapLogic?
In our company, we used the solution to build a SnapLogic pipeline in a non-production environment. Presently, our company is releasing it to the production environment. We have used SnapLogic in o...
What needs improvement with Spring Cloud Data Flow?
I would improve the dashboard features as they are not very user-friendly. Another area for improvement is the documentation, as it is not very precise. There are limited resources available on Spr...
What is your primary use case for Spring Cloud Data Flow?
I am a developer using Spring Cloud Dataflow. We primarily use it to convert our applications from monolithic to microservices. The solution is used for scheduling tasks in a specific order and ens...
What advice do you have for others considering Spring Cloud Data Flow?
My advice would be to thoroughly review the documentation and understand if Spring Cloud Dataflow is the right solution for your application. For applications with only one or two microservices, it...
 

Also Known As

DataFlow
No data available
 

Learn More

 

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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Find out what your peers are saying about SnapLogic vs. Spring Cloud Data Flow and other solutions. Updated: October 2024.
816,406 professionals have used our research since 2012.