Qlik Compose vs Spring Cloud Data Flow comparison

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2,050 views|1,547 comparisons
81% willing to recommend
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2,370 views|1,763 comparisons
100% willing to recommend
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Executive Summary

We performed a comparison between Qlik Compose and Spring Cloud Data Flow based on real PeerSpot user reviews.

Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration.
To learn more, read our detailed Data Integration Report (Updated: April 2024).
769,599 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"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 technical support is very good. I rate the technical support a ten out of ten.""I have found it to be a very good, stable, and strong product.""It can scale.""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.""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."

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"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 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 most valuable feature is real-time streaming.""The product is very user-friendly."

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Cons
"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.""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.""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.""I'd like to have access to more developer training materials.""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.""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.""There is some scope for improvement around the documentation, and a better UI would definitely help.""I believe that visual data flow management and the transformation function should be improved."

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"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation.""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.""On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."

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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."
  • "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."
  • More Qlik Compose Pricing and Cost Advice →

  • "This is an open-source product that can be used free of charge."
  • "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."
  • More Spring Cloud Data Flow Pricing and Cost Advice →

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    Questions from the Community
    Top Answer: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 cubes… more »
    Top Answer:The most valuable is its excellence as a graphical data representation tool and the versatility it offers, especially with drill-down capabilities.
    Top Answer:While they outperform Tableau, there's room for improvement in Qlik's pricing structures, especially for corporate clients like us.
    Top Answer:On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required. The online discussion forum for the tool should include possible questions… more »
    Top Answer:I used the solution for a payment platform we integrated with our organization. Our company had to use it since we had to integrate it with different payment platforms.
    Top Answer: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… more »
    Ranking
    20th
    out of 101 in Data Integration
    Views
    2,050
    Comparisons
    1,547
    Reviews
    10
    Average Words per Review
    460
    Rating
    7.7
    28th
    out of 101 in Data Integration
    Views
    2,370
    Comparisons
    1,763
    Reviews
    2
    Average Words per Review
    598
    Rating
    8.0
    Comparisons
    Also Known As
    Compose, Attunity Compose
    Learn More
    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.

    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.

    Sample Customers
    Poly-Wood
    Information Not Available
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm14%
    Manufacturing Company11%
    Computer Software Company10%
    Energy/Utilities Company6%
    VISITORS READING REVIEWS
    Financial Services Firm29%
    Computer Software Company16%
    Manufacturing Company7%
    Retailer7%
    Company Size
    REVIEWERS
    Small Business36%
    Midsize Enterprise9%
    Large Enterprise55%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise12%
    Large Enterprise70%
    VISITORS READING REVIEWS
    Small Business13%
    Midsize Enterprise10%
    Large Enterprise78%
    Buyer's Guide
    Data Integration
    April 2024
    Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration. Updated: April 2024.
    769,599 professionals have used our research since 2012.

    Qlik Compose is ranked 20th in Data Integration with 12 reviews while Spring Cloud Data Flow is ranked 28th in Data Integration with 5 reviews. Qlik Compose is rated 7.6, while Spring Cloud Data Flow is rated 8.0. The top reviewer of Qlik Compose writes "Easy matching and reconciliation of data". On the other hand, the top reviewer of Spring Cloud Data Flow writes "Provides ease of integration with other cloud platforms ". Qlik Compose is most compared with Qlik Replicate, Talend Open Studio, SSIS, Azure Data Factory and Oracle Data Integrator (ODI), whereas Spring Cloud Data Flow is most compared with Apache Flink, Google Cloud Dataflow, Apache Spark Streaming, Azure Data Factory and TIBCO BusinessWorks.

    See our list of best Data Integration vendors.

    We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.