AWS Glue vs Qlik Compose comparison

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12,051 views|8,582 comparisons
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2,162 views|1,624 comparisons
Comparison Buyer's Guide
Executive Summary

We performed a comparison between AWS Glue and Qlik Compose based on real PeerSpot user reviews.

Find out in this report how the two Cloud Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed AWS Glue vs. Qlik Compose Report (Updated: March 2024).
765,234 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
"AWS Glue is fast and managed by AWS. Hence, you don't have to worry about capacity and the performance of Glue jobs. It has integrations with other data stores of AWS. The product offers metadata management, logging, and ETL processing capabilities. It comes with a powerful feature, Glue Studio, which helps to do queries interactively within the community. It is a managed service and very secure. Another popular and mature service is S3.""Glue is a NoSQL-based data ETL tool that has some advantages over IIS and ISAs.""AWS Glue's best features are scalability and cloud-based features.""It is AWS-integrated. There is end-to-end integration with the other AWS services. It is also user-friendly.""The most valuable feature of AWS Glue is scalability.""AWS Glue is quite better than other tools, but you have to learn it properly before you start using it.""AWS Glue is a stable and easy-to-use solution.""Our entire use case was very easily handled or solved using this solution."

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"One of the most valuable features was the ability to integrate multiple source systems that mainly used structured IDBMS versions.""It is a scalable solution.""It's a stable solution.""It can scale.""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.""Qlik Compose is good enough. It is user-friendly and intuitive.""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.""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."

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Cons
"In terms of improvement, the performance of AWS Glue could be faster.""The solution's visual ETL tool is of no use for actual implementation.""There should be more connectors for different databases.""While working on AWS Glue, I could not find any training material for it.""One area that could be improved is the ETL view. The drag-and-drop interface is not as user-friendly as some other ETL tools.""Cost-wise, AWS Glue is expensive, so that's an area for improvement. The process for setting up the solution was also complex, which is another area for improvement.""AWS Glue is more costly compared to other tools like Airflow.""The solution’s stability could be improved."

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"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.""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 believe that visual data flow management and the transformation function should be improved.""There could be more customization options.""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.""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."

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Pricing and Cost Advice
  • "The pricing is a bit higher than other solutions like Athena and EC2. If the pricing becomes more scaled or flexible, it will be good because you have to pay 44 cents just for one DPU for an hour. If you increase DPUs to 5 or 10, the pricing gets multiplied. There are also some time limits like 0 to 10 minutes or 10 to 20 minutes. If the pricing is according to the minutes, it would be better because you have to limit your job to 10 minutes or 20 minutes."
  • "It is not expensive. AWS Glue works on the serverless architecture. We get charged for the time the server is up. For our use case, we have to use it once in a day, and it is not expensive for us."
  • "Its price is good. We pay as we go or based on the usage, which is a good thing for us because it is simple to forecast for the tool. It is good in terms of the financial planning of the company, and it is a good way to estimate the cost. It is also simple for our clients. In my opinion, it is one of the best tools in the market for ETL processes because of the fact that you pay as you use, which separates it from other big tools such as PowerCenter, Pentaho Data Integration, and Talend."
  • "Technical support is a paid service, and which subscription you have is dependent on that. You must pay one of them, and it ranges from $15,000 to $25,000 per year."
  • "This solution is affordable and there is an option to pay for the solution based on your usage."
  • "AWS Glue is quite costly, especially for small organizations."
  • "AWS Glue uses a pay-as-you-go approach which is helpful. The price of the overall solution is low and is a great advantage."
  • "The overall cost of AWS Glue could be better. It cost approximately $1,000 a month. There is paid support available from AWS Glue."
  • More AWS Glue 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 →

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    Questions from the Community
    Top Answer:AWS Glue and Azure Data factory for ELT best performance cloud services.
    Top Answer:We reviewed AWS Glue before choosing Talend Open Studio. AWS Glue is the managed ETL (extract, transform, and load) from Amazon Web Services. AWS Glue enables AWS users to create and manage jobs in… more »
    Top Answer:AWS Glue's main use case is for allowing users to discover, prepare, move, and integrate data from multiple sources. The product lets you use this data for analytics, application development, or… 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 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.
    Ranking
    1st
    Views
    12,051
    Comparisons
    8,582
    Reviews
    30
    Average Words per Review
    398
    Rating
    7.9
    18th
    out of 94 in Data Integration
    Views
    2,162
    Comparisons
    1,624
    Reviews
    10
    Average Words per Review
    460
    Rating
    7.7
    Comparisons
    Also Known As
    Compose, Attunity Compose
    Learn More
    Overview

    AWS Glue is a serverless cloud data integration tool that facilitates the discovery, preparation, movement, and integration of data from multiple sources for machine learning (ML), analytics, and application development. The solution includes additional productivity and data ops tooling for running jobs, implementing business workflows, and authoring.

    AWS Glue allows users to connect to more than 70 diverse data sources and manage data in a centralized data catalog. The solution facilitates visual creation, running, and monitoring of extract, transform, and load (ETL) pipelines to load data into users' data lakes. This Amazon product seamlessly integrates with other native applications of the brand and allows users to search and query cataloged data using Amazon EMR, Amazon Athena, and Amazon Redshift Spectrum.

    The solution also utilizes application programming interface (API) operations to transform users' data, create runtime logs, store job logic, and create notifications for monitoring job runs. The console of AWS Glue connects all of these services into a managed application, facilitating the monitoring and operational processes. The solution also performs provisioning and management of the resources required to run users' workloads in order to minimize manual work time for organizations.

    AWS Glue Features

    AWS Glue groups its features into four categories - discover, prepare, integrate, and transform. Within those groups are the following features:

    • Automatic schema discovery: AWS Glue crawlers connect to the organization's source or target data source through a prioritized list of classifiers to determine the schema for users' data. This feature creates metadata in companies' AWS Glue Data Catalog.

    • Schemas for data stream management: The AWS Glue Schema Registry enables users to validate and control the evolution of streaming data through registered Apache Avro schemas for no additional charge.

    • Automatic scaling based on workload: This feature dynamically scales resources up and down based on workload. The feature controls job resources, removing them depending on how much the workload can be split up.

    • FindMatches: This feature is for machine learning-based data deduplication and cleansing, and works by finding records that are imperfect matches of each other to remove useless data copies.

    • Edit, debug, and test ETL code: This feature helps users who have chosen to interactively develop their ETL code by providing development endpoints for editing, debugging, and testing the code it generates for them.

    • AWS Glue DataBrew: An interactive, point-and-click visual interface for specialists to clean and normalize data without the need to write any code.

    • AWS Glue Interactive Sessions: This feature simplifies the development of data integration jobs by enabling data engineers to interactively prepare and explore data.

    • AWS Glue Studio Job Notebooks: This AWS Glue feature provides serverless notebooks with minimal setup, allowing developers to start working in a timely manner.

    • Complex ETL pipeline building: This feature allows the product to be invoked on a schedule, on demand, or based on an event, allowing users to start multiple jobs in parallel or specify dependencies to build complex ETL pipelines.

    • AWS Glue Studio: This AWS Glue feature allows users to visually transform data through a drag-and-drop interface. The product automatically generates the code for ETL processes for users' data.

    AWS Glue Benefits

    AWS Glue offers a wide range of benefits for its users. These benefits include:

    • Users of other AWS products can easily onboard with AWS Glue, as it is integrated across a wide range of the company's services.

    • The solution is serverless, which allows for a lower total cost of ownership.

    • AWS Glue offers more power for users, as it automates much of the effort in building, maintaining, and running ETL jobs.

    • The product allows customers to easily discover and search across all their AWS datasets through AWS Glue Data Catalog.

    • AWS Glue does not require additional payment for managing and enforcing schemas for data streams.

    • The solution facilitates the authority of scalable ETL jobs for beginners and non-coding experts through a drag-and-drop interface.

    Reviews from Real Users

    Mustapha A., a cloud data engineer at Jems Groupe, likes AWS Glue because it is a product that is great for serverless data transformations.

    Liana I., CEO at Quark Technologies SRL, describes AWS Glue as a highly scalable, reliable, and beneficial pay-as-you-go pricing model.

    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.

    Sample Customers
    bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday
    Poly-Wood
    Top Industries
    REVIEWERS
    Computer Software Company47%
    Financial Services Firm18%
    Pharma/Biotech Company12%
    Consumer Goods Company6%
    VISITORS READING REVIEWS
    Financial Services Firm20%
    Computer Software Company13%
    Insurance Company7%
    Manufacturing Company7%
    VISITORS READING REVIEWS
    Financial Services Firm13%
    Manufacturing Company11%
    Computer Software Company11%
    Retailer6%
    Company Size
    REVIEWERS
    Small Business29%
    Midsize Enterprise13%
    Large Enterprise58%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise12%
    Large Enterprise73%
    REVIEWERS
    Small Business36%
    Midsize Enterprise9%
    Large Enterprise55%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise13%
    Large Enterprise70%
    Buyer's Guide
    AWS Glue vs. Qlik Compose
    March 2024
    Find out what your peers are saying about AWS Glue vs. Qlik Compose and other solutions. Updated: March 2024.
    765,234 professionals have used our research since 2012.

    AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while Qlik Compose is ranked 18th in Data Integration with 12 reviews. AWS Glue is rated 7.8, while Qlik Compose is rated 7.6. The top reviewer of AWS Glue writes "Provides serverless mechanism, easy data transformation and automated infrastructure management". On the other hand, the top reviewer of Qlik Compose writes "Easy matching and reconciliation of data". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, SSIS, Informatica Cloud Data Integration and Talend Open Studio, whereas Qlik Compose is most compared with Qlik Replicate, Talend Open Studio, Azure Data Factory, SSIS and Oracle Data Integrator (ODI). See our AWS Glue vs. Qlik Compose report.

    See our list of best Cloud Data Integration vendors.

    We monitor all Cloud 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.