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Dataloader.io vs Qlik Compose comparison

 

Comparison Buyer's Guide

Executive Summary

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

Dataloader.io
Ranking in Data Integration
48th
Average Rating
7.6
Reviews Sentiment
7.5
Number of Reviews
2
Ranking in other categories
No ranking in other categories
Qlik Compose
Ranking in Data Integration
45th
Average Rating
7.6
Reviews Sentiment
6.5
Number of Reviews
12
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of January 2026, in the Data Integration category, the mindshare of Dataloader.io is 0.5%, up from 0.1% compared to the previous year. The mindshare of Qlik Compose is 0.9%, down from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Qlik Compose0.9%
Dataloader.io0.5%
Other98.6%
Data Integration
 

Featured Reviews

reviewer2542599 - PeerSpot reviewer
Lead Database Administrator at a insurance company with 201-500 employees
Integrating external keys seamlessly while has transaction constraints
I find DataLoader's ability to easily integrate with external keys valuable, which is a bit more challenging with DBM. It provides automation for scheduling data loads, and we use the server's functionality for this. Additionally, DataLoader is cost-effective since it is free. As long as I have stable network access, uploading and downloading data is straightforward.
Sahil Taneja - PeerSpot reviewer
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.

Quotes from Members

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

Pros

"DataLoader is cost-effective since it is free."
"I find DataLoader's ability to easily integrate with external keys valuable, which is a bit more challenging with DBM."
"he product’s most valuable feature is ease of access."
"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."
"It is a scalable solution."
"It can scale."
"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."
"The technical support is very good. I rate the technical support a ten out of ten."
"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."
"The most valuable is its excellence as a graphical data representation tool and the versatility it offers, especially with drill-down capabilities."
"It's a stable solution."
 

Cons

"DataLoader has limitations, including constraints with file sizes and transactions."
"We need help with large data migrations. It only works well for a few thousand records or less than a million records."
"Dataloader has limitations, including constraints with file sizes and transactions. Additionally, at times it can be slow, and when integrating DBM, we find it more complex than Dataloader."
"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 should be proper documentation available for the implementation process."
"I believe that visual data flow management and the transformation function should be improved."
"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."
"There is some scope for improvement around the documentation, and a better UI would definitely help."
"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."
 

Pricing and Cost Advice

"The product is inexpensive and economical."
"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."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
15%
Government
12%
Manufacturing Company
9%
Insurance Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise3
Large Enterprise6
 

Questions from the Community

What is your experience regarding pricing and costs for Dataloader.io?
Dataloader.io is cost-effective, particularly since it is free.
What needs improvement with Dataloader.io?
DataLoader has limitations, including constraints with file sizes and transactions. Additionally, at times it can be slow, and when integrating DBM, we find it more complex than DataLoader.
What advice do you have for others considering Dataloader.io?
For small to mid-range businesses, DataLoader is perfectly fine, offering everything needed for uploading. On a scale of one to ten, I would rate DataLoader a seven or eight depending on specific n...
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...
 

Also Known As

No data available
Compose, Attunity Compose
 

Overview

 

Sample Customers

UCSF, Box, CareFusion, Unilever, Hershey's
Poly-Wood
Find out what your peers are saying about Dataloader.io vs. Qlik Compose and other solutions. Updated: January 2026.
881,114 professionals have used our research since 2012.