Google Cloud Dataflow vs Starburst Enterprise comparison

Google and Starburst are both solutions in the Streaming Analytics category. Google is ranked #9 with an average rating of 8.4, while Starburst is ranked #17 with an average rating of 8.5. Google holds a 3.9% mindshare in SA, compared to Starburst’s 2.8% mindshare. Additionally, 93% of Google users are willing to recommend the solution, compared to 100% of Starburst users who would recommend it.

Google Cloud Dataflow

Read 15 Google Cloud Dataflow reviews

2,566 Views
2,181 Comparison Views

93% willing to recommend

Starburst Enterprise

Read 2 Starburst Enterprise reviews

1,771 Views
1,027 Comparison Views

100% willing to recommend

Google Cloud Dataflow

Starburst Enterprise

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 17, 2024

Google Cloud Dataflow and Starburst Enterprise are competing in the data processing and analytics space. Starburst Enterprise has an edge due to its comprehensive feature depth and performance in distributed data queries.

Features: Google Cloud Dataflow integrates seamlessly with Google Cloud services like BigQuery. It offers scalability in stream and batch processing and automated resource management. Starburst Enterprise focuses on SQL-based distributed queries, offers broad data source connectivity, and executes federated queries. It is versatile in feature offerings.

Ease of Deployment and Customer Service: Starburst Enterprise offers flexible deployment across on-premises and cloud systems, supported by strong customer service. Google Cloud Dataflow simplifies initial setup due to its cloud-native design but requires complex configurations for advanced scenarios. Starburst provides better customer support and deployment flexibility.

Pricing and ROI: Google Cloud Dataflow is cost-effective for processing within Google's ecosystem, providing high returns when integrated services are used. Starburst Enterprise requires a higher initial investment but yields significant ROI by efficiently handling complex, multi-source data queries. While Google Cloud Dataflow is budget-friendly in specific environments, Starburst shows a strong ROI for high-demand data processing.

To learn more, read our detailed Google Cloud Dataflow vs. Starburst Enterprise Report (Updated: March 2026).

Buyer's Guide

Google Cloud Dataflow vs. Starburst Enterprise

March 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

Google Cloud Dataflow

Ranking in Streaming Analytics

9th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Starburst Enterprise

Ranking in Streaming Analytics

17th

Average Rating

8.6

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Science Platforms (16th)

Mindshare comparison

As of April 2026, in the Streaming Analytics category, the mindshare of Google Cloud Dataflow is 3.9%, down from 7.4% compared to the previous year. The mindshare of Starburst Enterprise is 2.8%, down from 3.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Google Cloud Dataflow	3.9%
Starburst Enterprise	2.8%
Other	93.3%

Streaming Analytics

Featured Reviews

reviewer2812851

Senior Customer Data Platform Specialist at a marketing services firm with 1,001-5,000 employees

Unified user personas have improved data workflows and support detailed monitoring and logging

Google Cloud has many streams and products. In Google Cloud, everything is translated in the backend, so we do not have to use services such as Apache Beam. When you want to use Google Cloud Functions, you write the code, and the backend talks to all the libraries or Apache, so we do not need to be concerned about those. We just need to use our functions that translate and have many tools and services readily available. Google Cloud Dataflow has made it very easy for detailed monitoring and logging features for pipeline performance assessment. For example, if I am using Google Cloud Functions, I can easily see what changes I have done and trace it properly. I can see what is happening with this script, how many users are affected, whether the script is working, what is failing, and how we can rectify issues with proper monitoring.

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KamleshPant

Senior Software Architect at USEReady

Connects to any data source from any region and offers unified access

There are no specific projects supported by Starburst regarding AI initiatives or machine learning projects. In the future, if we have all the data available, we can definitely capitalize on AI/ML and LLM capabilities to summarize data and gain insights. That's our future goal, but we haven't reached that point yet. There should be support for REST API data sources to access data from the web. We often have data coming in and communicate with data sources via REST API calls. I don't see that capability in Starburst currently; everything is through JDBC or ODBC. If Starburst could seamlessly access data using REST API capabilities, it would be a game-changer. The self-service data management features, like self-service materialized views, are great, but they can be a bit complex for basic users to understand.

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Quotes from Members

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

Pros

"The solution allows us to program in any language we desire."

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

"Google Cloud Dataflow has made it very easy for detailed monitoring and logging features for pipeline performance assessment."

"The service is relatively cheap compared to other batch-processing engines."

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

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

"It allows me to test solutions locally using runners like Direct Runner without having to start a Dataflow job, which can be costly."

"Migrating our batch processing jobs to Google Cloud Dataflow led to a reduction in cost by 70%."

More Google Cloud Dataflow pros

"It's very scalable, fast performing, and supports many catalogs."

"We have noticed improvements in performance using Starburst Enterprise. It handles complex data, including reading and partitioning files. We can add a new catalog to Starburst Enterprise by providing connection details and service account information. This allows us to integrate with existing tools, such as the Snowflake database, which we use for data protection in our project."

Cons

"Promoting the technology more broadly would help increase its adoption."

"The deployment time could also be reduced."

"The technical support has slight room for improvement."

"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."

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

"Google Cloud Dataflow should include a little cost optimization."

"The system could function in an automated fashion and provide suggestions based on past transactions to achieve better scalability."

"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."

More Google Cloud Dataflow cons

"There should be support for REST API data sources to access data from the web."

"Starburst Enterprise could improve by offering additional features similar to those provided by other SQL query tools. For example, incorporating functionalities like pivot tables would make it more feasible to use."

Pricing and Cost Advice

"The tool is cheap."

"Google Cloud is slightly cheaper than AWS."

"The solution is cost-effective."

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

"The solution is not very expensive."

"Google Cloud Dataflow is a cheap solution."

"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."

"I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of using Starburst Enterprise can vary based on the amount of data you're processing and the type of machines you opt for, whether on AWS or another cloud platform."

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Manufacturing Company

12%

Retailer

10%

Computer Software Company

Financial Services Firm

36%

Computer Software Company

Manufacturing Company

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	2
Large Enterprise	11

No data available

Questions from the Community

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 is your primary use case for Google Cloud Dataflow?

It is used for exporting data, such as customer clicks, customer interactions with emails, and link tracking. The Google Analytics streaming data is used to establish customer behavioral patterns.

See all answers

What is your experience regarding pricing and costs for Starburst Enterprise?

I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of us...

See all answers

What needs improvement with Starburst Enterprise?

See all answers

What is your primary use case for Starburst Enterprise?

We use Starburst with one client who is exploring their ecosystem to remove data silos and enable data access across departments. It's a very big ecosystem, like a finance institute. They are curre...

See all answers

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Compared 20% of the time

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Compared 8% of the time

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Compared 4% of the time

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Compared 18% of the time

Databricks vs Starburst Enterprise

Compared 15% of the time

Dremio vs Starburst Enterprise

Compared 8% of the time

Apache Flink vs Starburst Enterprise

Compared 6% of the time

Confluent vs Starburst Enterprise

Compared 4% of the time

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Product Reports

Buyer's Guide

Google Cloud Dataflow

April 2026

Download Google Cloud Dataflow product report

Buyer's Guide

Data Science Platforms

March 2026

Download Starburst Enterprise 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

Starburst Enterprise is a data analytics platform that enables organizations to access and analyze data from multiple sources, including cloud-based and on-premises data warehouses. It provides a single access point to all data sources, allowing users to query and analyze data without moving it between systems.

By providing a unified view, Starburst Enterprise helps organizations make better-informed decisions and improve operational efficiency, leading to better customer insights and more accurate forecasting. Overall, Starburst Enterprise is a powerful tool for organizations looking to unlock the full potential of their data.

Starburst

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. Starburst Enterprise

March 2026

Free Report: Google Cloud Dataflow vs. Starburst Enterprise

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