Dagster Labs vs Spring Cloud Data Flow comparison

Dagster Labs and Broadcom are both solutions in the Data Integration category. Dagster Labs is ranked #54 with an average rating of 7.8, while Broadcom is ranked #31 with an average rating of 7.5. Dagster Labs holds a 0.0% mindshare in DI, compared to Broadcom’s 1.0% mindshare. Additionally, 100% of Dagster Labs users are willing to recommend the solution, compared to 88% of Broadcom users who would recommend it.

Dagster Labs

Read 5 Dagster Labs reviews

1,499 Views
15 Comparison Views

100% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

4,093 Views
2,251 Comparison Views

88% willing to recommend

Dagster Labs

Spring Cloud Data Flow

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Executive Summary

We performed a comparison between Dagster Labs and Spring Cloud Data Flow based on real PeerSpot user reviews.

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To learn more, read our detailed Data Integration Report (Updated: June 2026).

Buyer's Guide

Data Integration

June 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

Dagster Labs

Ranking in Data Integration

54th

Average Rating

7.8

Reviews Sentiment

4.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Spring Cloud Data Flow

Ranking in Data Integration

31st

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (17th)

Mindshare comparison

As of July 2026, in the Data Integration category, the mindshare of Dagster Labs is 0.0%. The mindshare of Spring Cloud Data Flow is 1.0%, down from 1.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Spring Cloud Data Flow	1.0%
Dagster Labs	0.0%
Other	99.0%

Data Integration

Featured Reviews

Alekh Shrivastava

IT Consultant at a outsourcing company with 10,001+ employees

Automation and lineage visibility have transformed how our teams schedule and monitor ETL workflows

There are multiple products from Dagster Labs: Dagster Cloud, Dagster Labs, and sometimes it is quite confusing to choose which one for what purposes. I know there are some licensing buckets for small organizations, medium organizations, and bigger organizations, so the modeling and the cost estimation part could be more intuitive, making it easier for beginners to understand how much time and money they would save by onboarding Dagster Labs in their project. I deducted two points because I faced some challenges working with the Git repository integration with Dagster Labs due to some security keys or some weird issue. I had to get in a call with Dagster Labs subject matter expert, and we really struggled for two to three weeks because we could not establish the secure connection through that.

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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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Quotes from Members

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

Pros

"Dagster Labs has provided a good sense of the data pipeline I have been using, and I have started to trust it even more because I have full confidence in whether it has been updated correctly and if it has failed."

"Dagster Labs has impacted my organization positively by enabling faster project delivery since it has reduced a lot of manual efforts, especially the manual scheduling part."

"Dagster Labs has positively impacted our organization by making it much easier to create data pipelines, helping us create new use cases, and allowing us to transform all of the data we have into features, which Dagster Labs has greatly assisted with."

"As a product, it is one of the best I have had the pleasure to work with."

"Dagster Labs has positively impacted my organization because whenever there is a change in the data, it becomes easy for me to schedule the job, run the changes, and make changes to be imported to the slowly changing dimension tables."

"The product is very user-friendly."

"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."

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

"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."

"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 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 dashboards in Spring Cloud Dataflow are quite valuable."

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

More Spring Cloud Data Flow pros

Cons

"Additionally, the billing for Dagster Labs Cloud Plus is somewhat restrictive regarding the number of seats, which often pushes users towards the enterprise plan."

"I deducted two points because I faced some challenges working with the Git repository integration with Dagster Labs due to some security keys or some weird issue."

"There are many ways Dagster Labs can be improved. I believe the UI is very slow and it prevents loading state."

"Dagster Labs is currently providing a Dagster University course, but those offerings are somewhat high-level."

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

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

"I would improve the dashboard features as they are not very user-friendly."

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

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

"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."

"The documentation on offer is not that good."

"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."

More Spring Cloud Data Flow cons

Pricing and Cost Advice

Information not available

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

"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."

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

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Top Industries

By visitors reading reviews

Construction Company

30%

Comms Service Provider

Financial Services Firm

Retailer

Financial Services Firm

18%

Computer Software Company

11%

Retailer

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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

Questions from the Community

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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...

See all answers

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...

See all answers

Comparisons

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Compared 100% of the time

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Cloudera DataFlow vs Spring Cloud Data Flow

Compared 4% of the time

TIBCO Spotfire vs Spring Cloud Data Flow

Compared 4% of the time

Apache Spark Streaming vs Spring Cloud Data Flow

Compared 4% of the time

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Product Reports

Buyer's Guide

Data Integration

June 2026

Download Dagster Labs product report

Buyer's Guide

Spring Cloud Data Flow

June 2026

Download Spring Cloud Data Flow product report

Overview

Dagster Labs empowers data-centric enterprises to build, manage, and orchestrate complex data pipelines with ease. Its flexible architecture supports efficient data processing, enhancing productivity.

Dagster Labs provides a robust platform designed for performance and scalability, catering to developers and data engineers seeking to streamline data workflow management. It integrates seamlessly with modern data tools, facilitating efficient data pipeline execution and monitoring. Users benefit from its modular approach, enabling customization according to specific project requirements.

What are the key features of Dagster Labs?

Composable Workflows: Allows users to build and manage modular data pipelines with ease.
Dynamic Monitoring: Provides real-time insights into pipeline performance and health.
Integration Support: Seamlessly connects with popular tools like Apache Spark and Pandas.
Scalable Architecture: Ensures efficient handling of data processing workloads.
Flexible Design: Enables tailored solutions for specific data engineering needs.

What benefits and ROI should users look for in reviews?

Improved Efficiency: Users experience increased productivity with streamlined workflows.
Cost Savings: Optimized data pipelines reduce operational costs.
Enhanced Collaboration: Facilitates teamwork through shared workflows and tools.
Increased Agility: Quick adaptation to changing data requirements.
Reliable Performance: Consistent and dependable data processing capabilities.

Dagster Labs is particularly beneficial in industries such as finance, healthcare, and e-commerce, where data-driven insights are crucial. It enables financial institutions to process transactions swiftly, aids healthcare organizations in managing patient data securely, and helps e-commerce platforms optimize customer engagement through data analysis.

Dagster Labs

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.

Find out what your peers are saying about Informatica, Microsoft, Palantir and others in Data Integration. Updated: June 2026.

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