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Azure Data Factory vs Qlik Compose comparison

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Azure Data Factory Logo
27,271 views|22,407 comparisons
Qlik Compose Logo
2,710 views|2,037 comparisons
Featured Review
Find out what your peers are saying about Azure Data Factory vs. Qlik Compose and other solutions. Updated: January 2022.
564,997 professionals have used our research since 2012.
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The data copy template is a valuable feature.""In terms of my personal experience, it works fine.""The initial setup is very quick and easy.""One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect.""It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory.""The solution can scale very easily.""An excellent tool for pipeline orchestration.""On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good."

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"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."

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Cons
"We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on.""There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run.""It can improve from the perspective of active logging. It can provide active logging information.""Data Factory could be improved by eliminating the need for a physical data area. We have to extract data using Data Factory, then create a staging database for it with Azure SQL, which is very, very expensive. Another improvement would be lowering the licensing cost.""The solution needs to be more connectable to its own services.""There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base.""It would be better if it had machine learning capabilities.""The speed and performance need to be improved."

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

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Pricing and Cost Advice
  • "The price you pay is determined by how much you use it."
  • "Understanding the pricing model for Data Factory is quite complex."
  • "I would not say that this product is overly expensive."
  • "The licensing is a pay-as-you-go model, where you pay for what you consume."
  • "Our licensing fees are approximately 15,000 ($150 USD) per month."
  • "The licensing cost is included in the Synapse."
  • "It's not particularly expensive."
  • "Product is priced at the market standard."
  • More Azure Data Factory Pricing and Cost Advice →

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    Questions from the Community
    Top Answer: 
    AWS Glue and Azure Data factory for ELT best performance cloud services.
    Top Answer: 
    Azure Data Factory is flexible, modular, and works well. In terms of cost, it is not too pricey. It offers the stability and reliability I am looking for, good scalability, and is easy to set up and… more »
    Top Answer: 
    Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power… more »
    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… more »
    Top Answer: 
    I have found it to be a very good, stable, and strong product.
    Top Answer: 
    When you replicate data, you need to transform the data into formats that are easier for querying and reporting, or data warehousing. I think the set of transformation functions can be improved. In… more »
    Ranking
    2nd
    Views
    27,271
    Comparisons
    22,407
    Reviews
    23
    Average Words per Review
    506
    Rating
    7.7
    37th
    Views
    2,710
    Comparisons
    2,037
    Reviews
    1
    Average Words per Review
    599
    Rating
    6.0
    Comparisons
    Also Known As
    Compose, Attunity Compose
    Learn More
    Overview

    Create, schedule, and manage your data integration at scale with Azure Data Factory - a hybrid data integration (ETL) service. Work with data wherever it lives, in the cloud or on-premises, with enterprise-grade security.

    Qlik Compose comes in two offerings: Qlik Compose for Data Warehouses and Qlik Compose for Data Lakes. Qlik Compose for Data Warehouse automates and streamlines the design, creation, loading, management, and update of data warehouses including Amazon Redshift, Azure Synapse, Google BigQuery, Snowflake and Oracle. Qlik Compose for Data Lakes automates the process of providing continuously updated, accurate, and trusted data to big data platforms like Apache Hadoop, Cloudera Customer Data Platform and Databricks Unified Data Analytics Platform.

    Offer
    Learn more about Azure Data Factory
    Learn more about Qlik Compose
    Sample Customers
    Milliman, Pier 1 Imports, Rockwell Automation, Ziosk, Real Madrid
    Poly-Wood
    Top Industries
    REVIEWERS
    Computer Software Company29%
    Insurance Company12%
    Healthcare Company6%
    Logistics Company6%
    VISITORS READING REVIEWS
    Computer Software Company31%
    Comms Service Provider14%
    Financial Services Firm7%
    Energy/Utilities Company6%
    VISITORS READING REVIEWS
    Computer Software Company32%
    Comms Service Provider13%
    Manufacturing Company7%
    Healthcare Company7%
    Company Size
    REVIEWERS
    Small Business23%
    Midsize Enterprise28%
    Large Enterprise49%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise7%
    Large Enterprise75%
    No Data Available
    Find out what your peers are saying about Azure Data Factory vs. Qlik Compose and other solutions. Updated: January 2022.
    564,997 professionals have used our research since 2012.

    Azure Data Factory is ranked 2nd in Data Integration Tools with 21 reviews while Qlik Compose is ranked 37th in Data Integration Tools with 2 reviews. Azure Data Factory is rated 7.6, while Qlik Compose is rated 6.0. The top reviewer of Azure Data Factory writes "Easy to bring in outside capabilities, flexible, and works well". On the other hand, the top reviewer of Qlik Compose writes "Excellent data integration but needs better scheduling and monitoring features". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Talend Open Studio, Palantir Foundry and Alteryx Designer, whereas Qlik Compose is most compared with Qlik Replicate, Talend Open Studio, Palantir Foundry, WhereScape RED and Matillion ETL. See our Azure Data Factory vs. Qlik Compose report.

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    We monitor all Data Integration Tools 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.