Qlik Compose vs Spring Cloud Data Flow comparison

Qlik and Broadcom are both solutions in the Data Integration category. Qlik is ranked #48, while Broadcom is ranked #23 with an average rating of 7.8. Qlik holds a 1.0% 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

1,724 Views
1,500 Comparison Views

81% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

3,140 Views
1,601 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: March 2026).

Buyer's Guide

Qlik Compose vs. Spring Cloud Data Flow

March 2026

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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

48th

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

23rd

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (10th)

Mindshare comparison

As of March 2026, in the Data Integration category, the mindshare of Qlik Compose is 1.0%, 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 Mindshare Distribution
Product	Mindshare (%)
Spring Cloud Data Flow	1.1%
Qlik Compose	1.0%
Other	97.9%

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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NitinGoyal

Engineering Lead at Naukri.com

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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Quotes from Members

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

Pros

"One of the most valuable features was the ability to integrate multiple source systems that mainly used structured IDBMS versions."

"As long as you pick the solution that best fits with your requirements, you won't find that performance is a problem."

"As long as you pick the solution that best fits with your requirements, you won't find that performance is a problem. It's good."

"I have found it to be a very good, stable, and strong product."

"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."

"One of the most valuable features of this tool is its automation capabilities, allowing us to design the warehouse in an automated manner. Additionally, we can generate Data Lifecycle Policies (DLP) reports and efficiently implement updates and best practices based on proven design patterns."

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

"It can scale."

More Qlik Compose pros

"The most valuable feature is real-time streaming."

"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 most valuable feature is real-time streaming."

"The product is very user-friendly."

"This product will assist us in saving costs in many ways: No longer need to continue paying high fees for proprietary software, reduce the number of software engineers needed to support the product, and achieve faster time to market by using this product for our middleware."

"Overall, Spring Cloud Data Flow is a really good solution and a lot cheaper than a lot of infrastructure provided by big companies like Google or Amazon."

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

More Spring Cloud Data Flow pros

Cons

"It would be better if the first level of technical support were a bit more technically knowledgeable to solve the problem. I think they could also improve the injection of custom scripts. It is pretty difficult to add additional scripts. If the modeling doesn't give you what you want, and you want to change the script generated by the modeling, it is a bit more challenging than in most other products. It is very good with standard form type systems, but if you get a more complicated data paradigm, it tends to struggle with transforming that into a model."

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

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

"There is some scope for improvement around the documentation, and a better UI would definitely help."

"The solution has room for improvement in the ETL. They have an ETL, but when it comes to the monitoring portion, Qlik Compose doesn't provide a feature for monitoring."

"My issues with the solution's stability are owing to the fact that it has certain bugs causing issues in some functionalities that should be working."

More Qlik Compose cons

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

"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 documentation on offer is not that good."

"The visual user interface could use some help; it needs improvement."

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

"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."

"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."

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

More Spring Cloud Data Flow cons

Pricing and Cost Advice

"The price of the solution is expensive."

"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 solution provides value for money, and we are currently using its community edition."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

11%

Government

11%

Manufacturing Company

Construction Company

Financial Services Firm

17%

Computer Software Company

12%

Retailer

Manufacturing Company

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...

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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...

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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

Qlik Replicate vs Qlik Compose

Compared 14% of the time

Qlik Talend Cloud vs Qlik Compose

Compared 9% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Qlik Compose

Compared 9% of the time

WhereScape RED vs Qlik Compose

Compared 7% of the time

Airbyte Cloud vs Qlik Compose

Compared 6% of the time

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Apache Flink vs Spring Cloud Data Flow

Compared 17% of the time

TIBCO BusinessWorks vs Spring Cloud Data Flow

Compared 5% of the time

Apache Kafka vs Spring Cloud Data Flow

Compared 5% of the time

Apache Spark Streaming vs Spring Cloud Data Flow

Compared 4% of the time

IBM InfoSphere DataStage vs Spring Cloud Data Flow

Compared 4% of the time

More Spring Cloud Data Flow Competitors

Product Reports

Buyer's Guide

Qlik Compose

March 2026

Download Qlik Compose product report

Buyer's Guide

Spring Cloud Data Flow

March 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

March 2026

Free Report: Qlik Compose vs. Spring Cloud Data Flow

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