Qlik Compose vs Spring Cloud Data Flow comparison

Qlik and Broadcom are both solutions in the Data Integration category. Qlik is ranked #45, while Broadcom is ranked #20 with an average rating of 7.8. Qlik holds a 0.9% mindshare in DI, compared to Broadcom’s 1.1% mindshare. Additionally, 81% of Qlik users are willing to recommend the solution, compared to 88% of Broadcom users who would recommend it.

Qlik Compose

Read 12 Qlik Compose reviews

1,513 Views
1,316 Comparison Views

81% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

3,055 Views
1,436 Comparison Views

88% willing to recommend

Qlik Compose

Spring Cloud Data Flow

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

Qlik Compose and Spring Cloud Data Flow are competing in data management and integration, with Qlik Compose offering better pricing and scalability, while Spring Cloud Data Flow is superior in features and adaptability.

Features:Qlik Compose offers automated data migration, a comprehensive ETL solution, and data warehouse automation, enhancing efficiency and scalability. Spring Cloud Data Flow supports real-time data processing and boasts a microservices-based architecture, allowing flexibility and scalability in application development.

Room for Improvement:Qlik Compose could enhance its real-time processing capabilities and expand its integration with cloud services. Additionally, it would benefit from more community engagement and feature-rich updates to match competitors in dynamic environments. Spring Cloud Data Flow could improve its ease of use for non-specialists, optimize resource consumption during scale execution, and provide more straightforward deployment for users with limited hands-on expertise.

Ease of Deployment and Customer Service:Qlik Compose offers a user-friendly deployment model with robust technical support, facilitating a smooth transition. Spring Cloud Data Flow's container-based deployment offers greater customization but requires more technical expertise, accommodating complex deployments with higher flexibility.

Pricing and ROI:Qlik Compose provides competitive setup costs with a quick ROI due to efficient processes and reduced operational expenses. Spring Cloud Data Flow demands a higher initial investment, justified by its high-value return in dynamic environments that require adaptive data processing.

To learn more, read our detailed Qlik Compose vs. Spring Cloud Data Flow Report (Updated: December 2025).

Buyer's Guide

Qlik Compose vs. Spring Cloud Data Flow

December 2025

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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 Compose

Ranking in Data Integration

45th

Average Rating

7.6

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Spring Cloud Data Flow

Ranking in Data Integration

20th

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (11th)

Mindshare comparison

As of January 2026, in the Data Integration category, the mindshare of Qlik Compose is 0.9%, down from 1.1% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.1%, up from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Market Share Distribution
Product	Market Share (%)
Spring Cloud Data Flow	1.1%
Qlik Compose	0.9%
Other	98.0%

Data Integration

Featured Reviews

Sahil Taneja

Principal Consultant/Manager at Tenzing

Easy matching and reconciliation of data

The initial setup was easy for the data warehousing concept. But for a person who is new to ETL and warehousing concepts, it may take some time. If someone is familiar with these concepts, they could understand and learn the tool quickly. However, compared to other tools, the UI is complex. It would be helpful to have a better UI and documentation for new users. As of now, there is a challenge in learning the Compose tool for new users altogether. Qlik Compose was deployed on-premises. But the servers, like the SQL servers were maintained on the cloud—the managed instances.

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Lipika Naik

Senior Software Engineer at QBE Regional Insurance

Provides ease of integration with other cloud platforms

Spring Cloud Data Flow is a useful product if I consider how there are different providers with whom my company had to deal, and most of them offer cloud-based products. I can't explain any crucial circumstances where the product's integration capabilities were helpful, but the aforementioned details explain the scenario for which I used the solution. I was only involved with the development of the product and not with the data pipeline configuration phase. The use of Spring Cloud Data Flow greatly impacted projects' time to market since our company's intention was to actually deploy and ensure that the payment platform integrated with it, which was an easy process. The product's user interface was very intuitive. The tool was deployed in multiple environments, but I am not sure about the production. From the time I started taking up the job in my current organization, I saw that we have deployed the tool in multiple environments wherein the number of users extensively used the product in the UAT environment, which is one of the most stable environments. There were 20 different methods to test the tool. I wouldn't be able to tell you the production details of the tool as I was more part of the production deployment, but I can say that it was deployed with the intent of making it available for 10,000 users. Those who plan to use the product should enjoy the flexibility of the solution. I rate the tool a nine out of ten.

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Quotes from Members

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

Pros

"Qlik Compose is good enough. It is user-friendly and intuitive."

"The technical support is very good. I rate the technical support a ten out of ten."

"It can scale."

"I like modeling and code generation. It has become a pretty handy tool because of its short ideation to delivery time. From the time you decide you are modeling a data warehouse, and once you finish the modeling, it generates all the code, generates all the tables. All you have to do is tick a few things, and you can produce a fully functional warehouse. I also like that they have added all the features I have asked for over four years."

"The most valuable is its excellence as a graphical data representation tool and the versatility it offers, especially with drill-down capabilities."

"It is a scalable solution."

"It's a stable solution."

"There were many valuable features, such as extracting any data to put in the cloud. For example, Qlik was able to gather data from SAP and extract SAP data from the platforms."

More Qlik Compose pros

"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 most valuable feature is real-time streaming."

"The product is very user-friendly."

"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 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 dashboards in Spring Cloud Dataflow are quite valuable."

"The best thing I like about Spring Cloud Data Flow is its plug-and-play model."

Cons

"Qlik's ETL and data transformation could be better."

"There should be proper documentation available for the implementation process."

"There could be more customization options."

"When processing data from certain tables with a large volume of data, we encounter significant delays. For instance, when dealing with around one million records, it typically takes three to four hours. To address this, I aim to implement performance improvements across all tables, ensuring swift processing similar to those that are currently complete within seconds. The performance issue primarily arises when we analyze the inserts and updates from the source, subsequently dropping the table. While new insertions are handled promptly, updates are processed slowly, leading to performance issues. Despite consulting our Qlik vendors, they were unable to pinpoint the exact cause of this occurrence. Consequently, I am seeking ways to optimize performance within Qlik Compose, specifically concerning updates."

"I believe that visual data flow management and the transformation function should be improved."

"For more complex work, we are not using Qlik Compose because it cannot handle very high volumes at the moment. It needs the same batching capabilities that other ETL tools have. We can't batch the data into small chunks when transforming large amounts of data. It tries to do everything in one shot and that's where it fails."

"I'd like to have access to more developer training materials."

"It could enhance its capabilities in the realm of self-service options as currently, it is more suited for individuals with technical proficiency who can create pages using it."

More Qlik Compose cons

"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."

"I would improve the dashboard features as they are not very user-friendly."

"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."

"Some of the features, like the monitoring tools, are not very mature and are still evolving."

"Spring Cloud Data Flow is not an easy-to-use tool, so improvements are required."

"The solution's community support could be improved."

Pricing and Cost Advice

"While they outperform Tableau, there's room for improvement in Qlik's pricing structures, especially for corporate clients like us."

"On a scale of one to ten, where one is cheap, and ten is very expensive, I rate the solution a six."

"The price of the solution is expensive."

"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

15%

Government

12%

Manufacturing Company

Insurance Company

Financial Services Firm

20%

Computer Software Company

13%

Retailer

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	3
Large Enterprise	6

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	1
Large Enterprise	5

Questions from the Community

Which ETL tool would you recommend to populate data from OLTP to OLAP?

There are two products I know about * TimeXtender : Microsoft based, Transformation logic is quiet good and can easily be extended with T-SQL , Has a semantic layer that generates metat data for cu...

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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...

See all answers

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...

See all answers

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...

See all answers

Comparisons

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Compared 20% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Qlik Compose

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Qlik Talend Cloud vs Qlik Compose

Compared 11% of the time

Palantir Foundry vs Qlik Compose

Compared 9% of the time

Azure Data Factory vs Qlik Compose

Compared 7% of the time

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Apache Flink vs Spring Cloud Data Flow

Compared 26% of the time

TIBCO BusinessWorks vs Spring Cloud Data Flow

Compared 6% of the time

Apache Kafka vs Spring Cloud Data Flow

Compared 5% of the time

Apache Spark Streaming vs Spring Cloud Data Flow

Compared 5% of the time

IBM InfoSphere DataStage vs Spring Cloud Data Flow

Compared 4% of the time

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Product Reports

Buyer's Guide

Qlik Compose

January 2026

Download Qlik Compose product report

Buyer's Guide

Spring Cloud Data Flow

January 2026

Download Spring Cloud Data Flow product report

Also Known As

Compose, Attunity Compose

No data available

Overview

Qlik Sense is a powerful business intelligence tool that offers a range of features to help organizations make faster and more informed decisions. Its primary use cases include operational and financial dashboards, self-service reporting, and centralized access to cross-functional reports. The solution is praised for its mobile platform, ease of use, data-sharing capabilities, and extensibility.

Qlik Sense has helped organizations improve data literacy, reduce time consumed in complex reports, and provide widely available MI to senior stakeholders. It also enables self-service analytics, improves data quality and governance, enhances collaboration, and reduces costs.

Qlik

Spring Cloud Data Flow is a toolkit for building data integration and real-time data processing pipelines.
Pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. This makes Spring Cloud Data Flow suitable for a range of data processing use cases, from import/export to event streaming and predictive analytics. Use Spring Cloud Data Flow to connect your Enterprise to the Internet of Anything—mobile devices, sensors, wearables, automobiles, and more.

Broadcom

Sample Customers

Poly-Wood

Information Not Available

Buyer's Guide

Qlik Compose vs. Spring Cloud Data Flow

December 2025

Free Report: Qlik Compose vs. Spring Cloud Data Flow

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