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Google Cloud Dataflow vs Starburst Enterprise comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Google Cloud Dataflow
Ranking in Streaming Analytics
8th
Average Rating
7.8
Reviews Sentiment
7.0
Number of Reviews
10
Ranking in other categories
No ranking in other categories
Starburst Enterprise
Ranking in Streaming Analytics
12th
Average Rating
8.6
Number of Reviews
2
Ranking in other categories
Data Science Platforms (14th)
 

Mindshare comparison

As of November 2024, in the Streaming Analytics category, the mindshare of Google Cloud Dataflow is 8.3%, up from 6.6% compared to the previous year. The mindshare of Starburst Enterprise is 2.4%, up from 1.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

Tamer Talal - PeerSpot reviewer
A tool useful for data transmission and data storage that needs to improve its authentication area
The authentication part of the product is an area of concern where improvements are required. For some common users, the solution's authentication part is difficult to use. The scalability of the product is an area of concern where improvements are required. In the future, the product should be made available at a cheaper rate.
KamleshPant - PeerSpot reviewer
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.

Quotes from Members

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

Pros

"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."
"The solution allows us to program in any language we desire."
"The most valuable features of Google Cloud Dataflow are the integration, it's very simple if you have the complete stack, which we are using. It is overall very easy to use, user-friendly friendly, and cost-effective if you know how to use it. The solution is very flexible for programmers, if you know how to do scripts or program in Python or any other language, it's extremely easy to use."
"The product's installation process is easy...The tool's maintenance part is somewhat easy."
"Google Cloud Dataflow is useful for streaming and data pipelines."
"It is a scalable solution."
"The service is relatively cheap compared to other batch-processing engines."
"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

"The solution's setup process could be more accessible."
"Google Cloud Dataflow should include a little cost optimization."
"The technical support has slight room for improvement."
"There are certain challenges regarding the Google Cloud Composer which can be improved."
"When I deploy the product in local errors, a lot of errors pop up which are not always caught. The solution's error logging is bad. It can take a lot of time to debug the errors. It needs to have better logs."
"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."
"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."
"The authentication part of the product is an area of concern where improvements are required."
"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."
"There should be support for REST API data sources to access data from the web."
 

Pricing and Cost Advice

"Google Cloud is slightly cheaper than AWS."
"The solution is not very expensive."
"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."
"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."
"Google Cloud Dataflow is a cheap solution."
"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."
"The tool is cheap."
"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
17%
Retailer
12%
Computer Software Company
11%
Manufacturing Company
11%
Financial Services Firm
44%
Computer Software Company
10%
Government
4%
Energy/Utilities Company
4%
 

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.
What needs improvement with Google Cloud Dataflow?
The authentication part of the product is an area of concern where improvements are required. For some common users, the solution's authentication part is difficult to use. The scalability of the p...
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...
What needs improvement with Starburst Enterprise?
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 ...
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...
 

Also Known As

Google Dataflow
No data available
 

Learn More

 

Overview

 

Sample Customers

Absolutdata, Backflip Studios, Bluecore, Claritics, Crystalloids, Energyworx, GenieConnect, Leanplum, Nomanini, Redbus, Streak, TabTale
Information Not Available
Find out what your peers are saying about Google Cloud Dataflow vs. Starburst Enterprise and other solutions. Updated: October 2024.
816,406 professionals have used our research since 2012.