Qlik Compose vs Spring Cloud Data Flow comparison

Qlik and VMware are both solutions in the Data Integration category. Qlik is ranked #23 with an average rating of 7.9, while VMware is ranked #24 with an average rating of 7.7. Qlik holds a 1.1% mindshare in DI, compared to VMware’s 1.1% mindshare. Additionally, 81% of Qlik users are willing to recommend the solution, compared to 88% of VMware users who would recommend it.

Qlik Compose

Read 12 Qlik Compose reviews

1,451 Views
1,107 Comparison Views

81% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

1,421 Views
1,057 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: April 2025).

Buyer's Guide

Qlik Compose vs. Spring Cloud Data Flow

April 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

23rd

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

24th

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (9th)

Mindshare comparison

As of May 2025, in the Data Integration category, the mindshare of Qlik Compose is 1.1%, up from 0.9% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.1%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

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

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

"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 was the ability to integrate multiple source systems that mainly used structured IDBMS versions."

"It's a stable solution."

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

"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."

"It can scale."

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

More Qlik Compose pros

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

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

"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 product is very user-friendly."

"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 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."

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."

"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."

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

"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."

"There could be more customization options."

"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."

More Qlik Compose cons

"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."

"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."

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

"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."

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

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

Pricing and Cost Advice

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

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

"The price of the solution is expensive."

"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."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

Government

10%

Computer Software Company

Manufacturing Company

Financial Services Firm

26%

Computer Software Company

18%

Retailer

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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 do you like most about Qlik Compose?

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

See all answers

What is your experience regarding pricing and costs for Qlik Compose?

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

See all answers

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...

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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

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Compared 5% of the time

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Product Reports

Buyer's Guide

Qlik Compose

April 2025

Download Qlik Compose product report

Buyer's Guide

Spring Cloud Data Flow

April 2025

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.

VMware

Sample Customers

Poly-Wood

Information Not Available

Buyer's Guide

Qlik Compose vs. Spring Cloud Data Flow

April 2025

Free Report: Qlik Compose vs. Spring Cloud Data Flow

Find out what your peers are saying about Qlik Compose vs. Spring Cloud Data Flow and other solutions. Updated: April 2025.

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