Google Cloud Dataflow vs Qlik Talend Cloud comparison

Google and Qlik are both solutions in the Streaming Analytics category. Google is ranked #9 with an average rating of 8.1, while Qlik is ranked #11 with an average rating of 8.2. Google holds a 4.6% mindshare in SA, compared to Qlik’s 1.5% mindshare. Additionally, 93% of Google users are willing to recommend the solution, compared to 88% of Qlik users who would recommend it.

Google Cloud Dataflow

Read 14 Google Cloud Dataflow reviews

2,251 Views
1,891 Comparison Views

93% willing to recommend

Qlik Talend Cloud

Read 53 Qlik Talend Cloud reviews

5,551 Views
389 Comparison Views

88% willing to recommend

Google Cloud Dataflow

Qlik Talend Cloud

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Nov 18, 2025

Qlik Talend Cloud and Google Cloud Dataflow are major contenders in the data integration solutions category. Qlik Talend Cloud stands out in user satisfaction due to its pricing and support, while Google Cloud Dataflow excels in scalability thanks to its cloud-native design.

Features: Qlik Talend Cloud delivers comprehensive ETL capabilities, real-time data integration, and vast customization using Java, making it suitable for complex data needs. It provides a central metadata repository and robust data quality features for large enterprises. Google Cloud Dataflow utilizes Apache Beam's unified programming model, supporting both batch and stream processing with flexible language options. Its strong connectivity with Google services makes it appealing to those familiar with the Google ecosystem.

Room for Improvement: Qlik Talend Cloud faces issues with memory usage, stability, and documentation quality, leading to system crashes and memory problems. Access to technical support can also be inconsistent. Google Cloud Dataflow could enhance error logging, ease setup complexity, and improve configuration management.

Ease of Deployment and Customer Service: Qlik Talend Cloud offers flexible deployment across on-premises, hybrid, and private cloud environments, though setup can be complex, particularly on hybrid systems. Google Cloud Dataflow simplifies deployment on public clouds and benefits from strong integration with other Google Cloud Platform tools. Customer service is generally positive for both, with Google Cloud Dataflow's support often considered more consistent in quality.

Pricing and ROI: Qlik Talend Cloud's open-source options reduce setup costs, and its annual licensing provides expense predictability. Users report significant time and cost savings, citing high ROI. Google Cloud Dataflow's pricing is resource and data volume-driven, making it cost-effective against other engines. Although pricing fluctuates, users value the lower expenses and report substantial returns on investment.

To learn more, read our detailed Google Cloud Dataflow vs. Qlik Talend Cloud Report (Updated: December 2025).

Buyer's Guide

Google Cloud Dataflow vs. Qlik Talend Cloud

December 2025

Download the complete report

Helped 879,259 peers since 2012

Review summaries and opinions

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

ROI

Sentiment score

5.6

Google Cloud Dataflow was appreciated for cost savings and time efficiency, though some considered its impact not fully assessable yet.

Sentiment score

6.1

Qlik Talend Cloud users save time, reduce costs, and see quick ROI with improved efficiency and significant ETL process reduction.

No quotes available

For more quotes and insights, download the Google Cloud Dataflow report

It has helped us save a lot of time by automating repetitive data processes and reducing manual interventions.

Herivao Jus Winny

IT Consultant at a tech services company with 201-500 employees

We achieved around 20% to 30% time savings in the ETL process, reduced operational errors, and improved pipeline stability.

Henrique Fsantos

Data & Analytics Engineer at PicPay

We actually achieved the first 18 months worth of work in the first six months.

Jason Hale

Enterprise Architect at Waikato Regional Council

For more quotes and insights, download the Qlik Talend Cloud report

Customer Service

Sentiment score

6.6

Google Cloud Dataflow support varies, with users praising technical resolution but highlighting inconsistent response times and accessibility.

Sentiment score

7.0

Qlik Talend Cloud's customer service is friendly and responsive, yet improvements in complex cases and communication are needed.

The fact that no interaction is needed shows their great support since I don't face issues.

Jana Polianskaja

Data Engineer at Accenture

Google's support team is good at resolving issues, especially with large data.

Preethi Reddy

Senior Data Engineer at Accruent

Whenever we have issues, we can consult with Google.

Sunil Miragi

Senior Software Engineer at Dun & Bradstreet

For more quotes and insights, download the Google Cloud Dataflow report

The support team is responsive when we raise issues, and they usually provide clear guidance or solutions.

Herivao Jus Winny

IT Consultant at a tech services company with 201-500 employees

I would rate the technical support from Talend Data Quality as an 8 or 9.

Karthik Babu

Senior Consultant at a tech services company with 201-500 employees

The customer support for Talend Data Integration is very good; whenever I raise a ticket in the customer portal, I immediately receive an email, and follow-up communication is prompt.

Pabin Vaz

Assistant Consultant at a tech vendor with 10,001+ employees

For more quotes and insights, download the Qlik Talend Cloud report

Scalability Issues

Sentiment score

7.3

Google Cloud Dataflow excels in scalability and efficiency, making it ideal for real-time data processing and dynamic needs.

Sentiment score

7.0

Qlik Talend Cloud excels in scalability and cloud performance, effectively handling large data volumes with infrastructure and resource support.

Google Cloud Dataflow has auto-scaling capabilities, allowing me to add different machine types based on pace and requirements.

Jana Polianskaja

Data Engineer at Accenture

As a team lead, I'm responsible for handling five to six applications, but Google Cloud Dataflow seems to handle our use case effectively.

Sunil Miragi

Senior Software Engineer at Dun & Bradstreet

Google Cloud Dataflow can handle large data processing for real-time streaming workloads as they grow, making it a good fit for our business.

Preethi Reddy

Senior Data Engineer at Accruent

For more quotes and insights, download the Google Cloud Dataflow report

By using features like job parallelization and modular design, we can expand our data flows without having to rebuild everything.

Herivao Jus Winny

IT Consultant at a tech services company with 201-500 employees

The scalability of Talend Data Integration is good; if it weren't scalable, it wouldn't be reliable.

Pabin Vaz

Assistant Consultant at a tech vendor with 10,001+ employees

Its scalability is good, as Qlik Talend Cloud can handle large amounts of data and grow as needed, especially in cloud environments.

Henrique Fsantos

Data & Analytics Engineer at PicPay

For more quotes and insights, download the Qlik Talend Cloud report

Stability Issues

Sentiment score

8.3

Google Cloud Dataflow is stable, reliably handles tasks, and benefits from automatic scaling, with minor issues on complex tasks.

Sentiment score

7.1

Qlik Talend Cloud is stable, highly rated, with minor bugs mainly due to external factors, not inherent flaws.

I have not encountered any issues with the performance of Dataflow, as it is stable and backed by Google services.

Jana Polianskaja

Data Engineer at Accenture

The job we built has not failed once over six to seven months.

Sunil Miragi

Senior Software Engineer at Dun & Bradstreet

The automatic scaling feature helps maintain stability.

Preethi Reddy

Senior Data Engineer at Accruent

For more quotes and insights, download the Google Cloud Dataflow report

We have not encountered many issues with remote engines, and the interfaces are properly developed.

Selim Seddiki

Consultant en intelligence décisionnelle at VO2 Group

Once the jobs are properly designed and deployed, they run reliably without major issues.

Herivao Jus Winny

IT Consultant at a tech services company with 201-500 employees

For more quotes and insights, download the Qlik Talend Cloud report

Room For Improvement

Google Cloud Dataflow needs better Kafka integration, improved error logs, reduced startup time, and enhanced Python SDK features.

Qlik Talend Cloud needs enhanced stability, integration, support, and usability to overcome technical and performance challenges and improve functionality.

Outside of Google Cloud Platform, it is problematic for others to use it and may require promotion as an actual technology.

Jana Polianskaja

Data Engineer at Accenture

Dealing with a huge volume of data causes failure due to array size.

Sunil Miragi

Senior Software Engineer at Dun & Bradstreet

I would like to see improvements in consistency and flexibility for schema design for NoSQL data stored in wide columns.

Preethi Reddy

Senior Data Engineer at Accruent

For more quotes and insights, download the Google Cloud Dataflow report

On the flip side, that is one of its amazing strengths, as you are not locked into a very rigid way of doing something.

Jason Hale

Enterprise Architect at Waikato Regional Council

It would be great to have more ready-to-use connectors for modern cloud and SaaS platforms.

Herivao Jus Winny

IT Consultant at a tech services company with 201-500 employees

Talend Data Integration can be improved by reducing the license cost, as it is a bit high compared to other tools, which can be a burden for small-scale companies wanting to buy a license.

Pabin Vaz

Assistant Consultant at a tech vendor with 10,001+ employees

For more quotes and insights, download the Qlik Talend Cloud report

Setup Cost

Google Cloud Dataflow is praised for cost-effectiveness and scalability, offering competitive pricing influenced by pipeline complexity and company size.

Qlik Talend Cloud pricing varies, with potential cost-effectiveness, but complex licensing can lead to unexpected higher expenses.

It is part of a package received from Google, and they are not charging us too high.

Sunil Miragi

Senior Software Engineer at Dun & Bradstreet

For more quotes and insights, download the Google Cloud Dataflow report

My experience with Talend Data Integration's pricing, setup cost, and licensing is that it is a bit higher compared to other tools, making it not very affordable.

Pabin Vaz

Assistant Consultant at a tech vendor with 10,001+ employees

The license cost has increased significantly, leading many companies to seek more profitable options in the market.

reviewer2784657

ETL developer at a tech vendor with 10,001+ employees

For more quotes and insights, download the Qlik Talend Cloud report

Valuable Features

Google Cloud Dataflow offers seamless integration, multi-language support, scalability, and serverless data handling for efficient batch and streaming processes.

Qlik Talend Cloud enhances real-time data integration with extensive connectors, advanced tools, and flexible, reusable data pipelines for efficiency.

It supports multiple programming languages such as Java and Python, enabling flexibility without the need to learn something new.

Jana Polianskaja

Data Engineer at Accenture

The integration within Google Cloud Platform is very good.

Sunil Miragi

Senior Software Engineer at Dun & Bradstreet

Google Cloud Dataflow's features for event stream processing allow us to gain various insights like detecting real-time alerts.

Preethi Reddy

Senior Data Engineer at Accruent

For more quotes and insights, download the Google Cloud Dataflow report

By automating daily data loading processes, we reduced manual effort by around three or four hours per day, which saved roughly 60 to 80 hours per month.

Herivao Jus Winny

IT Consultant at a tech services company with 201-500 employees

We perform profiling prior to data quality and post-data quality, and based on that, we determine how much it has improved to measure the efficiency of Talend Data Quality cleaning tools.

Karthik Babu

Senior Consultant at a tech services company with 201-500 employees

The feature that has made the biggest difference for me in Qlik Talend Cloud is the scheduling and automation, which helps me run ETL jobs automatically without manual work.

Henrique Fsantos

Data & Analytics Engineer at PicPay

For more quotes and insights, download the Qlik Talend Cloud report

Categories and Ranking

Google Cloud Dataflow

Ranking in Streaming Analytics

9th

Average Rating

8.0

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Qlik Talend Cloud

Ranking in Streaming Analytics

11th

Average Rating

8.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Integration (9th), Data Quality (3rd), Data Scrubbing Software (1st), Master Data Management (MDM) Software (3rd), Cloud Data Integration (7th), Data Governance (8th), Cloud Master Data Management (MDM) (4th), Integration Platform as a Service (iPaaS) (9th)

Mindshare comparison

As of December 2025, in the Streaming Analytics category, the mindshare of Google Cloud Dataflow is 4.6%, down from 7.8% compared to the previous year. The mindshare of Qlik Talend Cloud is 1.5%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Market Share Distribution
Product	Market Share (%)
Google Cloud Dataflow	4.6%
Qlik Talend Cloud	1.5%
Other	93.9%

Streaming Analytics

Featured Reviews

Jana Polianskaja

Data Engineer at Accenture

Build Scalable Data Pipelines with Apache Beam and Google Cloud Dataflow

As a data engineer, I find several features of Google Cloud Dataflow particularly valuable. The ability to test solutions locally using Direct Runner is crucial for development, allowing me to validate pipelines without incurring the costs of full Dataflow jobs. The unified programming model for both batch and streaming processing is exceptional - requiring only minor code adjustments to optimize for either mode. This flexibility extends to language support, with robust implementations in both Java and Python, allowing teams to leverage their existing expertise. The platform's comprehensive monitoring capabilities are another standout feature. The intuitive interface, Grafana integration, and extensive service connectivity make troubleshooting and performance tracking highly efficient. Furthermore, seamless integration with Google Cloud Composer (managed Airflow) enables sophisticated orchestration of data pipelines.

Read full review

Herivao Jus Winny

IT Consultant at a tech services company with 201-500 employees

Has automated recurring data flows and improved accuracy in reporting

The best features of Talend Data Integration are its rich set of components that let you connect to almost any data design intuitive and its strong automation and scheduling capabilities. The TMap component is especially valuable because it allows flexible transformation, joins, and filtering in a single place. I also rely a lot on context variables to manage different environments like Dev, Test, and production, without changing the code. The error handling and logging tools are very helpful for monitoring and troubleshooting, which makes the workflow more reliable. Talend Data Integration has helped our company by automating and standardizing data processes. Before, many of these tasks were done manually, which took more time and often led to errors. With Talend Data Integration, we built automated pipelines that extract, clean, and load data consistently. This not only saves hours of manual effort, but also improves the accuracy and reliability of data. As a result, business teams had faster access to trustworthy information for reporting and decision making, which directly improved efficiency and productivity. Talend Data Integration has had a measurable impact on our organization. By automating daily data loading processes, we reduced manual effort by around three or four hours per day, which saved roughly 60 to 80 hours per month. We also improved data accuracy. Error rates dropped by more than 70% because validation rules were built into the jobs. In addition, reporting teams now receive fresh data at least 50% faster, which means they can make decisions earlier and with more confidence. Overall, Talend Data Integration has increased both efficiency and reliability in our data workflows.

Read full review

See which vendors are best for you

Use our free recommendation engine to learn which Streaming Analytics solutions are best for your needs.

See recommendations

879,259 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

19%

Manufacturing Company

12%

Retailer

11%

Healthcare Company

Financial Services Firm

13%

Computer Software Company

11%

Comms Service Provider

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	2
Large Enterprise	10

By reviewers
Company Size	Count
Small Business	20
Midsize Enterprise	11
Large Enterprise	18

Questions from the Community

What do you like most about Google Cloud Dataflow?

The product's installation process is easy...The tool's maintenance part is somewhat easy.

See all answers

What is your experience regarding pricing and costs for Google Cloud Dataflow?

Pricing is normal. It is part of a package received from Google, and they are not charging us too high.

See all answers

What needs improvement with Google Cloud Dataflow?

It can be improved in several ways. The system could function in an automated fashion and provide suggestions based on past transactions to achieve better scalability. Implementing AI-based suggest...

See all answers

What do you like most about Talend Data Quality?

The most valuable feature lies in the capability to assign data quality issues to different stakeholders, facilitating the tracking and resolution of defective work.

See all answers

What needs improvement with Talend Data Quality?

I don't use the automated rule management feature in Talend Data Quality that much, so I cannot provide much feedback. I may not know what Talend Data Quality can improve for data quality. I'm not ...

See all answers

What is your primary use case for Talend Data Quality?

It is for consistency, mainly; data consistency and data quality are our main use cases for the product. Data consistency is the primary purpose we use it for, as we have written rules in Talend Da...

See all answers

Comparisons

Databricks vs Google Cloud Dataflow

Compared 29% of the time

Apache Flink vs Google Cloud Dataflow

Compared 20% of the time

Apache NiFi vs Google Cloud Dataflow

Compared 11% of the time

Spring Cloud Data Flow vs Google Cloud Dataflow

Compared 6% of the time

Amazon MSK vs Google Cloud Dataflow

Compared 5% of the time

More Google Cloud Dataflow Competitors

Informatica Intelligent Data Management Cloud (IDMC) vs Qlik Talend Cloud

Compared 10% of the time

SSIS vs Qlik Talend Cloud

Compared 4% of the time

Collibra Platform vs Qlik Talend Cloud

Compared 4% of the time

Melissa Data Quality vs Qlik Talend Cloud

Compared 3% of the time

Ataccama ONE Platform vs Qlik Talend Cloud

Compared 3% of the time

More Qlik Talend Cloud Competitors

Product Reports

Buyer's Guide

Google Cloud Dataflow

December 2025

Download Google Cloud Dataflow product report

Buyer's Guide

Qlik Talend Cloud

December 2025

Download Qlik Talend Cloud product report

Also Known As

Google Dataflow

Talend Data Quality, Talend Data Management Platform, Talend MDM Platform, Talend Data Streams, Talend Data Integration, Talend Data Integrity and Data Governance

Overview

Google Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.

Google

Qlik Talend Cloud provides robust data integration tools tailored for efficient management of large volumes, offering real-time data access, Java integration, and custom code capabilities for developers.

Qlik Talend Cloud is known for its extensive connectivity options, enabling seamless integration across different platforms, such as S3, Redshift, Oracle, and SQL Server. The central repository facilitates consistent metadata access throughout organizations, enhancing collaboration. Despite its strengths in advanced monitoring, automation, and user-friendly drag-and-drop interfaces, users face challenges with installation stability, technical support, documentation inconsistencies, and complexities in learning. Performance concerns also include multitasking limitations and excessive memory usage. The platform's licensing costs can be prohibitive for smaller companies, while demands for improved data governance and intuitive code management continue. Its applications in healthcare data parsing, ETL task automation, and diverse data platform integration demonstrate its utility, although there's a constant demand for better scalability and efficient transformations.

What are the key features?

Seamless Real-Time Data Access: Ensures that users can access the latest information across systems without delays for better decision-making.
Java Integration: Facilitates smooth incorporation of Java components into workflows, broadening development options.
Custom Code Development: Offers flexibility to develop tailored solutions to meet specific integration scenarios.
Vast Connectors: Enhances connectivity between multiple platforms, supporting comprehensive data integration strategies.
Central Repository: Allows for uniform metadata access across departments, promoting cohesive data management practices.
Automation and Monitoring: Streamlines workflows with advanced automation and monitoring, reducing manual intervention and errors.

What benefits and ROI should users evaluate?

Improved Data Quality: Tools for data matching and error handling ensure high-quality, reliable data for analytics and reporting.
Efficient Workflow Streamlining: Drag-and-drop interfaces and automation features simplify complex workflows, enhancing operational efficiency.
Enhanced Business Insights: By integrating diverse data sources, businesses can derive deeper insights and ensure compliance through better data management.
Cost Management: Although some users find licensing expensive, comprehensive feature sets aimed at improving data processes can justify costs.
Community Support: Users benefit from active community forums that provide assistance, although technical support also necessitates enhancements.

In specialized industries like healthcare, users leverage Qlik Talend Cloud for data integration and transformation, aiding in compliance and analytics. Compatibility with cloud and on-premises systems ensures adaptability to complex data tasks, facilitating business application development. Organizations focus on enhanced data ingestion and quality checks for comprehensive solutions.

Qlik

Sample Customers

Absolutdata, Backflip Studios, Bluecore, Claritics, Crystalloids, Energyworx, GenieConnect, Leanplum, Nomanini, Redbus, Streak, TabTale

Aliaxis, Electrocomponents, M¾NCHENER VEREIN, The Sunset Group

Buyer's Guide

Google Cloud Dataflow vs. Qlik Talend Cloud

December 2025

Free Report: Google Cloud Dataflow vs. Qlik Talend Cloud

Find out what your peers are saying about Google Cloud Dataflow vs. Qlik Talend Cloud and other solutions. Updated: December 2025.

DOWNLOAD NOW

879,259 professionals have used our research since 2012.

See our Google Cloud Dataflow vs. Qlik Talend Cloud report.

See our list of best Streaming Analytics vendors and best Cloud Data Integration vendors.

We monitor all Streaming Analytics 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.