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Qlik Replicate 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

Qlik Replicate
Ranking in Data Integration
16th
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
18
Ranking in other categories
No ranking in other categories
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 July 2025, in the Data Integration category, the mindshare of Qlik Replicate is 3.0%, up from 2.9% 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

KrishnaBaddam - PeerSpot reviewer
Lightweight tool, ensures that data is replicated across different systems and simplify complex tasks such as defining relationships
Qlik Compose is something that will automate user's overall data modernization. Here data modernization includes data modeling, ETL jobs, etc. But the advantage is users can automate the overall process of data engineering and data modeling through Qlik Compose. I think that's useful when users are able to manage 60% of the workload automated. That will be very useful. That's fantastic. Replicate does not have a great AI capability. AI capabilities are present in Qlik Sense. Qlik Replicate is a very light tool. It is only meant to capture data from the log files, get the data, and transfer it, read that table structure, create the table structure, and transfer the data whenever there is a change. So, it basically integrates with the kernel of the operating system. The way it works is that these replicate tools will integrate with the kernel of the operating system, and they will access the redo log files of the database. The redo log should have access to all the files of the structure of the schema, too. So, using that technique, they redo all the data structures, create a similar structure, and replicate the structure in the target schema, table, and database. After that is done, it will start tracing the instances that are happening. For example, if data is inserted into the table, then an insert is fired on the statement on the table. So, that particular insert is captured. And based on that insert statement, it will pull the SQL query and say, "Okay, there is an insert. I need to get that data." It will get the data from the redo log itself rather than going to a database. Then, it will just pass that transaction into the target system, where it will just insert the data. And this happens instantaneously, within a microsecond. So, if there is an insert, an update, or a delete, everything is transferred immediately. It is picked from the redo log because it comes to the redo log, and then the redo log sends it to Qlik Replicate and Replicate to the target system on which Replicate is installed.
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 cost is under control with this solution, unlike other services where it's not."
"The system is basically user-driven, mostly operating as a local platform."
"The CDC and the flexibility to use QVD as a source are the most valuable features of Qlik Replicate."
"Great with replicating and updating records."
"A pretty good series of connectors is one of the best features of Qlik Replicate."
"The most useful functions of Qlik Replicate are the data manipulation to transformations."
"Qlik Replicate stands out with its cutting-edge technology and its ability to handle diverse data management tasks. This powerful tool allows us to efficiently and swiftly load data into various data stores or destinations, while also enabling easy distribution across different endpoints. A notable feature is its capability to reload data from multiple sources by creating multiple tasks within a brief timeframe of fifteen to twenty minutes. This eliminates the need for manual intervention and ensures quick data loading from different tables."
"It's very user-friendly when it comes to settings and configuration. It also offers very detailed logging about warnings and errors."
"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 dashboards in Spring Cloud Dataflow are quite valuable."
"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."
"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 product is very user-friendly."
"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."
 

Cons

"Support-wise, this solution is in need of improvement."
"There is complexity involved in the licensing part of this system."
"Support response times could be improved as there are sometimes delays in receiving replies to support cases."
"It would be better if the solution’s pricing were more obvious."
"The UI and data version control can be improved."
"It's not possible to replicate the QVC files in data analytics."
"In the next release, I would like to see closer integration with data catalyst."
"I am not very comfortable with Qlik support as it often goes in loops. Even priority tickets, which should be resolved in minutes, can take days."
"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 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."
"I would improve the dashboard features as they are not very user-friendly."
"The solution's community support could be improved."
"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 is not an easy-to-use tool, so improvements are required."
 

Pricing and Cost Advice

"Qlik Replicate is not expensive, compared to GoldenGate."
"On a scale from one to ten, where one is cheap, and ten is expensive, I rate Qlik Replicate's pricing a nine out of ten."
"Qlik Replicate is mainly suited for large companies. However, it is too costly for small businesses. Its pricing is high."
"Pricing for this solution is very reasonable."
"Unlike Azure, where you pay based on consumption, Qlik Replicate seems to charge per endpoint."
"Overall, Qlik is an expensive solution. You need to pay for all additional features that you would like to use."
"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."
"The solution provides value for money, and we are currently using its community edition."
"This is an open-source product that can be used free of charge."
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Top Industries

By visitors reading reviews
Financial Services Firm
19%
Insurance Company
11%
Computer Software Company
10%
Manufacturing Company
9%
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 Qlik Replicate?
The main valuable feature is its real-time change data capture (CDC) capabilities, which process data with minimal latency. There is not much delay. It also performs well with batch-wise data appli...
What needs improvement with Qlik Replicate?
Qlik Replicate could be improved in the next release by incorporating more monitoring options to monitor the logs. Currently, log monitoring is not easily accessible, so there should be improvement...
What is your primary use case for Qlik Replicate?
My customer's main use case for Qlik Replicate is with one of the payment banks in India. We have implemented this Replicate project for their source data migration to cloud solutions. They wanted ...
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

Replicate, Qlik Replicate
No data available
 

Overview

 

Sample Customers

American Cancer Society, Fanzz, SM Retail, Smart Modular, Tangerine Bank, Wellcare
Information Not Available
Find out what your peers are saying about Qlik Replicate vs. Spring Cloud Data Flow and other solutions. Updated: July 2025.
861,524 professionals have used our research since 2012.