Google Cloud Dataflow vs Upsolver comparison

Google and Upsolver are both solutions in the Streaming Analytics category. Google is ranked #7 with an average rating of 8.0, while Upsolver is ranked #17 with an average rating of 8.5. Google holds a 7.1% mindshare in SA, compared to Upsolver’s 0.3% mindshare. Additionally, 92% of Google users are willing to recommend the solution, compared to 100% of Upsolver users who would recommend it.

Google Cloud Dataflow

Read 13 Google Cloud Dataflow reviews

3,122 Views
2,513 Comparison Views

92% willing to recommend

Upsolver

Read 2 Upsolver reviews

101 Views
70 Comparison Views

100% willing to recommend

Google Cloud Dataflow

Upsolver

Comparison Buyer's Guide

Download the report

Executive Summary

We performed a comparison between Google Cloud Dataflow and Upsolver based on real PeerSpot user reviews.

Find out in this report how the two Streaming Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Google Cloud Dataflow vs. Upsolver Report (Updated: April 2025).

Buyer's Guide

Google Cloud Dataflow vs. Upsolver

April 2025

Download the complete report

Helped 850,028 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:

Categories and Ranking

Google Cloud Dataflow

Ranking in Streaming Analytics

7th

Average Rating

8.0

Reviews Sentiment

7.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Upsolver

Ranking in Streaming Analytics

17th

Average Rating

8.6

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

Data Integration (37th)

Mindshare comparison

As of May 2025, in the Streaming Analytics category, the mindshare of Google Cloud Dataflow is 7.1%, down from 7.2% compared to the previous year. The mindshare of Upsolver is 0.3%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

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

Snehasish Das

Technology Leader at eTCaaS

Allows for data to be moved across platforms and different data technologies

The most prominent feature of Upsolver is its function as an ETL tool, allowing data to be moved across platforms and different data technologies. Upsolver does this in a quick time, unlike traditional processes which are time-consuming. Additionally, it offers scalability for large volumes of data, with performance and ease of cloud-native integration.

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

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

"The most valuable features of Google Cloud Dataflow are scalability and connectivity."

"I would rate the overall solution a ten out of ten."

"The integration within Google Cloud Platform is very good."

"The support team is good and it's easy to use."

"Google Cloud Dataflow is useful for streaming and data pipelines."

"The best feature of Google Cloud Dataflow is its practical connectedness."

"I don't need a server running all the time while using the tool. It is also easy to setup. The product offers a pay-as-you-go service."

More Google Cloud Dataflow pros

"The most prominent feature of Upsolver is its function as an ETL tool, allowing data to be moved across platforms and different data technologies."

"Customer service is excellent, and I would rate it between eight point five to nine out of ten."

"It was easy to use and set up, with a nearly no-code interface that relied mostly on drag-and-drop functionality."

Cons

"The deployment time could also be reduced."

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

"The solution's setup process could be more accessible."

"There are certain challenges regarding the Google Cloud Composer which can be improved."

"I would like Google Cloud Dataflow to be integrated with IT data flow and other related services to make it easier to use as it is a complex tool."

"They should do a market survey and then make improvements."

"Google Cloud Data Flow can improve by having full simple integration with Kafka topics. It's not that complicated, but it could improve a bit. The UI is easy to use but the experience could be better. There are other tools available that do a better job."

"Occasionally, dealing with a huge volume of data causes failure due to array size."

More Google Cloud Dataflow cons

"There is room for improvement in query tuning."

"Upsolver excels in ETL and data aggregation, while ThoughtSpot is strong in natural language processing for querying datasets. Combining these tools can be very effective: Upsolver handles aggregation and ETL, and ThoughtSpot allows for natural language queries. There’s potential for highlighting these integrations in the future."

"On the stability side, I would rate it seven out of ten. Using multiple cloud providers and data engineering technologies creates complexity, and managing different plugins is not always easy, but they are working on it."

Pricing and Cost Advice

"Google Cloud Dataflow is a cheap solution."

"Google Cloud is slightly cheaper than AWS."

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a seven to eight out of ten."

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate Google Cloud Dataflow's pricing a four out of ten."

"The solution is not very expensive."

"The tool is cheap."

"The price of the solution depends on many factors, such as how they pay for tools in the company and its size."

"The solution is cost-effective."

"Upsolver is affordable at approximately $225 per terabyte per year."

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

850,028 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

17%

Manufacturing Company

12%

Retailer

11%

Computer Software Company

10%

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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?

I am not sure, as we built only one job, and it is running on a daily basis. Everything else is managed using BigQuery schedulers and Talend. However, occasionally, dealing with a huge volume of da...

See all answers

What is your experience regarding pricing and costs for Upsolver?

Upsolver is affordable at approximately $225 per terabyte per year. Compared to what I know from others, it's cheaper than many other products.

See all answers

What needs improvement with Upsolver?

There is room for improvement in query tuning. Upsolver could do a more in-depth analysis in employing machine power, such as CPU and memory, to enhance query performance. Furthermore, allocating C...

See all answers

What is your primary use case for Upsolver?

I am working as a consultant and currently have my own consultancy services. I provide services to companies that are data-heavy and looking for data engineering solutions for their business needs....

See all answers

Comparisons

Databricks vs Google Cloud Dataflow

Compared 39% of the time

Apache Flink vs Google Cloud Dataflow

Compared 15% of the time

Apache NiFi vs Google Cloud Dataflow

Compared 12% of the time

Amazon MSK vs Google Cloud Dataflow

Compared 9% of the time

Spring Cloud Data Flow vs Google Cloud Dataflow

Compared 7% of the time

More Google Cloud Dataflow Competitors

Databricks vs Upsolver

Compared 100% of the time

More Upsolver Competitors

Product Reports

Buyer's Guide

Google Cloud Dataflow

April 2025

Download Google Cloud Dataflow product report

Buyer's Guide

Data Integration

March 2025

Download Upsolver product report

Also Known As

Google Dataflow

No data available

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

Upsolver's mission is to turn engineering-intensive data lakes into easy-to-use repositories that serve 50X more data professionals compared to the status-quo today. Upsolver cuts 95% from the tedious process of preparing event data for analytics and machine learning, using a visual SQL-based interface, a cloud-native data platform and deep technology for stream-processing, indexing and eventually-consistent file systems.

Upsolver

Sample Customers

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

Information Not Available

Buyer's Guide

Google Cloud Dataflow vs. Upsolver

April 2025

Free Report: Google Cloud Dataflow vs. Upsolver

Find out what your peers are saying about Google Cloud Dataflow vs. Upsolver and other solutions. Updated: April 2025.

DOWNLOAD NOW

850,028 professionals have used our research since 2012.

See our Google Cloud Dataflow vs. Upsolver report.

See our list of best Streaming Analytics 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.