Spring Cloud Data Flow vs Starburst Enterprise comparison

Why PeerSpot?

Broadcom and Starburst are both solutions in the Streaming Analytics category. Broadcom is ranked #17 with an average rating of 8.0, while Starburst is ranked #24. Broadcom holds a 2.6% mindshare in SA, compared to Starburst’s 2.1% mindshare. Additionally, 88% of Broadcom users are willing to recommend the solution, compared to 100% of Starburst users who would recommend it.

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

5,525 Views
1,658 Comparison Views

88% willing to recommend

Starburst Enterprise

Read 2 Starburst Enterprise reviews

2,660 Views
1,436 Comparison Views

100% willing to recommend

Spring Cloud Data Flow

Starburst Enterprise

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 17, 2024

Spring Cloud Data Flow and Starburst Enterprise compete in data processing and analytics. Spring Cloud Data Flow has a slight edge in flexibility and support, while Starburst Enterprise is favored for its feature richness, especially for advanced analytical needs.

Features: Spring Cloud Data Flow integrates easily with Spring projects and enhances both streaming and batch processing. It seamlessly orchestrates data pipelines. Starburst Enterprise performs high-performance analytics across a unified data platform, is compatible with multiple data sources, and offers real-time processing.

Ease of Deployment and Customer Service: Spring Cloud Data Flow benefits from a straightforward deployment process using cloud-native microservices architectures. Starburst Enterprise, while requiring more complex deployment, provides superior support tailored to its comprehensive and analytics-focused platform.

Pricing and ROI: Spring Cloud Data Flow is cost-effective with attractive setup costs, offering good ROI due to its open-source nature and ease of use. Starburst Enterprise involves higher initial expense but delivers significant ROI through premium analytics features and performance enhancements.

To learn more, read our detailed Spring Cloud Data Flow vs. Starburst Enterprise Report (Updated: September 2026).

Buyer's Guide

Spring Cloud Data Flow vs. Starburst Enterprise

September 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

Spring Cloud Data Flow

Ranking in Streaming Analytics

17th

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Integration (33rd)

Starburst Enterprise

Ranking in Streaming Analytics

24th

Average Rating

8.6

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Science Platforms (21st)

Mindshare comparison

As of November 2026, in the Streaming Analytics category, the mindshare of Spring Cloud Data Flow is 2.6%, down from 4.6% compared to the previous year. The mindshare of Starburst Enterprise is 2.1%, down from 3.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Spring Cloud Data Flow	2.6%
Starburst Enterprise	2.1%
Other	95.3%

Streaming Analytics

Featured Reviews

NitinGoyal

Engineering Lead at Naukri.com

Has a plug-and-play model and provides good robustness and scalability

The solution's community support could be improved. I don't know why the Spring Cloud Data Flow community is not very strong. Community support is very limited whenever you face any problem or are stuck somewhere. I'm not sure whether it has improved in the last six months because this pipeline was set up almost two years ago. I struggled with that a lot. For example, there was limited support whenever I got an exception and sought help from Stack Overflow or different forums. Interacting with Kubernetes needs a few certificates. You need to define all the certificates within your application. With the help of those certificates, your Java application or Spring Cloud Data Flow can interact with Kubernetes. I faced a lot of hurdles while placing those certificates. Despite following the official documentation to define all the replicas, readiness, and liveliness probes within the Spring Cloud Data Flow application, it was not working. So, I had to troubleshoot while digging in and debugging the internals of Spring Cloud Data Flow at that time. It was just a configuration mismatch, and I was doing nothing weird. There was a small spelling difference between how Spring Cloud Data Flow was expecting it and how I passed it. I was just following the official documentation.

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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

"There are a lot of options in Spring Cloud. It's flexible in terms of how we can use it. It's a full infrastructure."

"Overall, Spring Cloud Data Flow is a really good solution and a lot cheaper than a lot of infrastructure provided by big companies like Google or Amazon."

"The dashboards in Spring Cloud Dataflow are quite valuable."

"This product will assist us in saving costs in many ways: No longer need to continue paying high fees for proprietary software, reduce the number of software engineers needed to support the product, and achieve faster time to market by using this product for our middleware."

"The most valuable feature is real-time streaming."

"The ease of deployment on Kubernetes, the seamless integration for orchestration of various pipelines, and the visual dashboard that simplifies operations even for non-specialists such as quality analysts."

"The solution's most valuable feature is that it allows us to use different batch data sources, retrieve the data, and then do the data processing, after which we can convert and store it in the target."

"The best thing I like about Spring Cloud Data Flow is its plug-and-play model."

More Spring Cloud Data Flow 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

"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."

"There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or refreshing the dashboard."

"The documentation on offer is not that good."

"The visual user interface could use some help; it needs improvement."

"Some of the features, like the monitoring tools, are not very mature and are still evolving."

"Spring Cloud Data Flow is not an easy-to-use tool, so improvements are required."

"The solution's community support could be improved."

"Spring Cloud Data Flow could improve the user interface. We can drag and drop in the application for the configuration and settings, and deploy it right from the UI, without having to run a CI/CD pipeline. However, that does not work with Kubernetes, it only works when we are working with jars as the Spring Cloud Data Flow applications."

More Spring Cloud Data Flow 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

"This is an open-source product that can be used free of charge."

"The solution provides value for money, and we are currently using its community edition."

"If you want support from Spring Cloud Data Flow there is a fee. The Spring Framework is open-source and this is a free solution."

"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

15%

Outsourcing Company

Computer Software Company

Comms Service Provider

Financial Services Firm

33%

Computer Software Company

Manufacturing Company

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	1
Large Enterprise	5

No data available

Questions from the Community

What needs improvement with Spring Cloud Data Flow?

There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or r...

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What is your primary use case for Spring Cloud Data Flow?

We had a project for content management, which involved multiple applications each handling content ingestion, transformation, enrichment, and storage for different customers independently. We want...

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What advice do you have for others considering Spring Cloud Data Flow?

I would definitely recommend Spring Cloud Data Flow. It requires minimal additional effort or time to understand how it works, and even non-specialists can use it effectively with its friendly docu...

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Product Reports

Buyer's Guide

Spring Cloud Data Flow

October 2026

Download Spring Cloud Data Flow product report

Buyer's Guide

Data Science Platforms

October 2026

Download Starburst Enterprise product report

Overview

Spring Cloud Data Flow is a toolkit for building data integration and real-time data processing pipelines.
Pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. This makes Spring Cloud Data Flow suitable for a range of data processing use cases, from import/export to event streaming and predictive analytics. Use Spring Cloud Data Flow to connect your Enterprise to the Internet of Anything—mobile devices, sensors, wearables, automobiles, and more.

Broadcom

Starburst Enterprise optimizes data processing for businesses, offering a robust platform tailored for efficient data handling. Ideal for tech-savvy audiences, it powers seamless data analysis and management.

Starburst Enterprise provides an advanced infrastructure that simplifies querying massive data sets from a variety of sources. Its integration capabilities allow users to access and analyze data without extensive data movement, ensuring cost-effective operations and speedy insights. Businesses can leverage comprehensive data analytics strategies, significantly enhancing their decision-making processes while minimizing latency.

What are the key features of Starburst Enterprise?

Data Federation: Connects disparate data sources without consolidation.
High-Performance Query: Delivers fast, interactive SQL analytics even on diverse data sets.
Security and Access Control: Ensures data is protected with robust security protocols and user management systems.
Scalability: Capable of handling increasing workloads efficiently.

What benefits and ROI should users look for?

Cost Efficiency: Reduces data warehousing costs by querying data at its source.
Time Savings: Accelerates data access and query responses, improving productivity.
Scalability: Supports growing data needs effortlessly, reducing infrastructure investments.

In industries like finance and retail, Starburst Enterprise is implemented to streamline big data operations, enhance customer experiences, and facilitate better risk management. Its ability to integrate with existing infrastructures allows for seamless adoption into company operations, delivering substantial analytical advantages.

Starburst

Buyer's Guide

Spring Cloud Data Flow vs. Starburst Enterprise

September 2026

Free Report: Spring Cloud Data Flow vs. Starburst Enterprise

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