Qlik Compose vs StreamSets comparison

Qlik and IBM are both solutions in the Data Integration category. Qlik is ranked #52, while IBM is ranked #24 with an average rating of 9.5. Qlik holds a 0.8% mindshare in DI, compared to IBM’s 1.1% mindshare. Additionally, 81% of Qlik users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

Qlik Compose

Read 12 Qlik Compose reviews

2,621 Views
2,123 Comparison Views

81% willing to recommend

StreamSets

Read 21 StreamSets reviews

4,142 Views
3,189 Comparison Views

100% willing to recommend

Qlik Compose

StreamSets

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

StreamSets and Qlik Compose compete in the data integration category. StreamSets seems to have the upper hand in terms of ease of use and integration capabilities, while Qlik Compose excels in automation and data management.

Features: StreamSets is known for its ease of use, wide connector range, and ability to handle both batch and streaming data effectively. Users highlight the Control Hub and Data Collector for offering a user-friendly drag-and-drop interface. Seamless integration with platforms like AWS and Azure is highly valued. Qlik Compose, on the other hand, shines in automation, enabling warehouse design with minimal coding. It provides excellent data integration and management features, supporting synchronization across databases.

Room for Improvement: StreamSets users report issues with integration beyond Java platforms and call for better memory management and simpler logging. They also see room for enhancing security and usability, alongside documentation and community support improvements. Qlik Compose users desire stronger monitoring and data transformation capabilities. They look for enhanced handling of high-volume data, better custom coding language integration, and more intuitive user experiences.

Ease of Deployment and Customer Service: StreamSets offers flexibility across public, hybrid, and on-premises cloud environments. Technical support reviews vary, from effective to requiring patience, with improvements desired in response times and communication. Qlik Compose primarily deploys on-premises and in private clouds, with users often relying on community and web resources. Technical support needs to be more user-friendly and responsive.

Pricing and ROI: StreamSets has multiple pricing models, including a free version and paid editions with advanced features, but costs are high for small businesses, leading to calls for more flexible pricing. Despite this, users find significant ROI in time savings and better data integration. Qlik Compose's pricing is also considered high, especially for corporate clients, suggesting a need for more competitive options. Both solutions offer valuable features that impact perceived value and ROI differently for users.

To learn more, read our detailed Qlik Compose vs. StreamSets Report (Updated: August 2026).

Buyer's Guide

Qlik Compose vs. StreamSets

August 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

52nd

Average Rating

7.6

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

StreamSets

Ranking in Data Integration

24th

Average Rating

8.4

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2026, in the Data Integration category, the mindshare of Qlik Compose is 0.8%, down from 1.1% compared to the previous year. The mindshare of StreamSets is 1.1%, down from 1.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
StreamSets	1.1%
Qlik Compose	0.8%
Other	98.1%

Data Integration

Featured Reviews

Susheel A

Director - Metrics & Analytics at a computer software company with 1,001-5,000 employees

Efficient data warehouse automation with robust features, but may require enhancements in user-friendly self-service options and pricing flexibility for broader corporate appeal

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. When it comes to end users who may lack technical expertise, they are limited to toggling between existing developments. To empower end users to make critical changes without relying heavily on technical expertise, it would be beneficial to introduce more user-friendly features for development and modification. If it could incorporate correlation analysis capabilities into its platform, especially in a user-friendly manner, it would greatly enhance the tool's overall utility and make it an even more outstanding solution. There is a room for improvement regarding stability.

Read full review

SrinivasanSankar

Enterprise Solutions Architect at a energy/utilities company with 1,001-5,000 employees

Enables effective batch loading with visual interface and enterprise support

One issue I observed with StreamSets is that the memory runs out quickly when processing large volumes of data. Because of this memory issue, we have to upgrade our EC2 boxes in the Amazon AWS infrastructure. I had to switch to a new EC2 box, even though the processor was not fully utilized. It would be beneficial if StreamSets addressed any potential memory leak issues to prevent unnecessary upgrades. Additionally, it would be a great enhancement if StreamSets could produce a lineage graph to visualize how the data has passed through the system.

Read full review

Quotes from Members

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

Pros

"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."

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

"It's a stable solution."

"It can scale."

"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."

More Qlik Compose pros

"What I love the most is that StreamSets is very light. It's a containerized application. It's easy to use with Docker. If you are a large organization, it's very easy to use Kubernetes."

"It has helped us in moving into the data analytics world at a faster pace than any other tool would have done."

"The most valuable feature is the pipelines because they enable us to pull in and push out data from different sources and to manipulate and clean things up within them."

"The Ease of configuration for pipes is amazing. It has a lot of connectors. Mainly, we can do everything with the data in the pipe. I really like the graphical interface too"

"The most valuable would be the GUI platform that I saw. I first saw it at a special session that StreamSets provided towards the end of the summer. I saw the way you set it up and how you have different processes going on with your data. The design experience seemed to be pretty straightforward to me in terms of how you drag and drop these nodes and connect them with arrows."

"StreamSets has definitely helped us in getting the information into our data lake very quickly, in terms of ingestion, and the most important thing is it has helped us from a resourcing point of view because you can easily upskill a BI or ETL resource without any programming knowledge to work with this, which has drastically reduced the time that we are spending on workloads by 60% to 70% as well as reducing the time spent on ingestion by 30%."

"For me, the most valuable features in StreamSets have to be the Data Collector and Control Hub, but especially the Data Collector. That feature is very elegant and seamlessly works with numerous source systems."

"This product was a lot easier to use than the one we had before it, and it took us half an hour and we were set up and running it the first time."

More StreamSets pros

Cons

"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."

"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."

"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."

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

"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."

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

"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."

More Qlik Compose cons

"Currently, we can only use the query to read data from SAP HANA. What we would like to see, as soon as possible, is the ability to read from multiple tables from SAP HANA."

"We've seen a couple of cases where it appears to have a memory leak or a similar problem."

"In terms of the product, I don't think there is any room for improvement because it is very good. One small area of improvement that is very much needed is on the knowledge base side. Sometimes, it is not very clear how to set up a certain process or a certain node for a person who's using the platform for the first time."

"There are a few things that can be better."

"If you use JDBC Lookup, for example, it generally takes a long time to process data."

"The design experience is the bane of our existence because their documentation is not the best. Even when they update their software, they don't publish the best information on how to update and change your pipeline configuration to make it conform to current best practices. We don't pay for the added support. We use the "freeware version." The user community, as well as the documentation they provide for the standard user, are difficult, at best."

"The monitoring visualization is not that user-friendly. It should include other features to visualize things, like how many records were streamed from a source to a destination on a particular date."

"One issue I observed with StreamSets is that the memory runs out quickly when processing large volumes of data. Because of this memory issue, we have to upgrade our EC2 boxes in the Amazon AWS infrastructure."

More StreamSets 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."

"There are different versions of the product. One is the corporate license version, and the other one is the open-source or free version. I have been using the corporate license version, but they have recently launched a new open-source version so that anybody can create an account and use it. The licensing cost varies from customer to customer. I don't have a lot of input on that. It is taken care of by PMO, and they seem fine with its pricing model. It is being used enterprise-wide. They seem to have got a good deal for StreamSets."

"It's not so favorable for small companies."

"We are running the community version right now, which can be used free of charge."

"The licensing is expensive, and there are other costs involved too. I know from using the software that you have to buy new features whenever there are new updates, which I don't really like. But initially, it was very good."

"The overall cost is very flexible so it is not a burden for our organization... However, the cost should be improved. For small and mid-size organizations it might be a challenge."

"There are two editions, Professional and Enterprise, and there is a free trial. We're using the Professional edition and it is competitively priced."

"The pricing is too fixed. It should be based on how much data you need to process. Some businesses are not so big that they process a lot of data."

"StreamSets is an expensive solution."

More StreamSets pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Comms Service Provider

10%

Construction Company

10%

Manufacturing Company

Financial Services Firm

12%

Comms Service Provider

Manufacturing Company

Construction 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	9
Midsize Enterprise	2
Large Enterprise	11

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...

See all answers

What needs improvement with StreamSets?

See all answers

What is your primary use case for StreamSets?

We are using StreamSets for batch loading.

See all answers

What advice do you have for others considering StreamSets?

If asked, I definitely recommend StreamSets to other users. My overall rating for the solution is nine.

See all answers

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Compared 10% of the time

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Compared 9% of the time

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Compared 8% of the time

WhereScape RED vs Qlik Compose

Compared 6% of the time

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Compared 9% of the time

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Compared 6% of the time

SSIS vs StreamSets

Compared 5% of the time

Confluent vs StreamSets

Compared 5% of the time

Spring Cloud Data Flow vs StreamSets

Compared 5% of the time

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Product Reports

Buyer's Guide

Qlik Compose

July 2026

Download Qlik Compose product report

Buyer's Guide

StreamSets

July 2026

Download StreamSets product report

Also Known As

Compose, Attunity Compose

No data available

Overview

Qlik Compose enhances data management with ETL capabilities, data integration with CDC, and real-time replication. Its intuitive interface enables easy data modeling and automation, supporting various database integrations.

Qlik Compose is designed for efficient data preparation, migration, and warehouse generation. It incorporates ETL functionalities and data integration with CDC, allowing users to effortlessly create data marts without code. Its automation features facilitate warehouse design while graphical representations and connectivity options increase versatility across multiple sources. Users value its stability, scalability, and the support provided, although improvements in ETL functionalities, performance for large datasets, and NoSQL integration are needed. The solution is widely used in business intelligence with tools like Qlik Replicate for real-time data replication and requires direct SQL for complex transformations.

What are the key features of Qlik Compose?

ETL Capabilities: Simplifies data extraction, transformation, and loading
Data Integration with CDC: Enables real-time data replication
Intuitive Interface: Facilitates easy data modeling and automation
Drag-and-Drop Functionality: Streamlines data task management
Auto-Mapping: Enhances integration of multiple data sources
No-Code Data Marts Creation: Reduces dependency on technical skills

What benefits should users consider in the reviews?

Stability and Scalability: Reliable functioning for growing data needs
Technical Support: Availability of assistance for troubleshooting
Real-Time Replication Capabilities: Efficient data processing and analytics
Low-Code Development: Simplifies complex data handling processes

In industries, Qlik Compose is implemented for enhancing data preparation, migration, and warehousing. It is used in small projects or straightforward data integration tasks and supports business intelligence efforts by offering low-code capabilities, enabling companies to deliver tailored analytics solutions efficiently.

Qlik

StreamSets streamlines data pipeline creation, connecting data from multiple sources to destinations like cloud platforms with minimal coding. Its centralized platform and intuitive design enhance ETL and data migration processes.

StreamSets integrates seamlessly with analytics platforms, offering tools such as Data Collector and Control Hub to facilitate data ingestion, transformation, and machine learning integrations. Its user-friendly interface and ready connectors aid in configuring complex data pipelines. With built-in data drift resilience and scheduling options, users experience efficient, scalable data management, despite challenges like latency in cloud storage and interface enhancement needs. Users often employ StreamSets for batch loading, real-time data processing, and smart data pipeline management, offering comprehensive data integration solutions.

What are the key features of StreamSets?

Data Collector: Enables streamlined data collection and processing.
Control Hub: Centralizes management of data pipelines.
Minimal Coding: Simplifies pipeline configuration with limited code requirement.
Data Drift Resilience: Adapts to changes in data patterns effectively.

What benefits should users look for?

Time-Saving: Efficient processes reduce manual effort.
Scalability: Easily manages large datasets.
Integration: Connects with leading analytics and cloud platforms.
Real-Time Processing: Supports continuous data delivery for timely insights.

In industries like finance and technology, StreamSets supports data migration, machine learning integrations, and analytics by simplifying data transformation and enhancing decision-making capabilities through its robust pipeline management.

IBM

Sample Customers

Poly-Wood

Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge

Buyer's Guide

Qlik Compose vs. StreamSets

August 2026

Free Report: Qlik Compose vs. StreamSets

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