SAS Data Management vs Spring Cloud Data Flow comparison

SAS and Broadcom are both solutions in the Data Integration category. SAS is ranked #27 with an average rating of 10.0, while Broadcom is ranked #31 with an average rating of 7.5. SAS holds a 1.2% mindshare in DI, compared to Broadcom’s 1.0% mindshare. Additionally, 88% of SAS users are willing to recommend the solution, compared to 88% of Broadcom users who would recommend it.

SAS Data Management

Read 19 SAS Data Management reviews

4,656 Views
2,607 Comparison Views

88% 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

SAS Data Management

Spring Cloud Data Flow

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

SAS Data Management and Spring Cloud Data Flow compete in the data management and integration tool space. SAS Data Management holds an advantage for comprehensive data handling, while Spring Cloud Data Flow stands out with real-time processing capabilities.

Features: SAS Data Management provides a comprehensive suite for cross-functional data management, including tools for ETL, CDC, and data federation. It offers robust data quality and integration with a flexible language and advanced reporting features. Spring Cloud Data Flow supports real-time streaming, microservices orchestration, and strong integration capabilities, with easy visualization and custom component development.

Room for Improvement: SAS Data Management is criticized for its high cost, inflexible licensing, and complex installation processes. Users also seek improved graphical interfaces and cloud integration. Spring Cloud Data Flow requires better documentation, especially for Kubernetes setups, improvements in the user interface, and stronger community support.

Ease of Deployment and Customer Service: SAS Data Management primarily relies on on-premises setups, with customer service support being less comprehensive post-acquisition. Spring Cloud Data Flow offers flexible deployment for on-premises and private cloud, though its support and community engagement need enhancement.

Pricing and ROI: SAS Data Management is suitable for large enterprises due to its high cost but offers significant ROI in regulated industries. Spring Cloud Data Flow is open-source and cost-effective, with lower pricing appealing to those seeking flexibility, but support services incur additional fees.

To learn more, read our detailed SAS Data Management vs. Spring Cloud Data Flow Report (Updated: June 2026).

Buyer's Guide

SAS Data Management vs. Spring Cloud Data Flow

June 2026

Download the complete report

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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

SAS Data Management

Ranking in Data Integration

27th

Average Rating

8.6

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Data Quality (6th), Data Governance (24th)

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 SAS Data Management is 1.2%, up from 0.9% compared to the previous year. 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 (%)
SAS Data Management	1.2%
Spring Cloud Data Flow	1.0%
Other	97.8%

Data Integration

Featured Reviews

Namanjbaraiya Baru

Biostatistician at Lambda Therapeutic Research Ltd.

Data management has ensured compliant clinical trial datasets and supports reliable analysis

SAS Data Management's best feature is first, data reliability because SAS Data Management is a very trusted platform. The other valuable feature is data cleaning and the compliance that SAS Data Management provides. I can connect SAS Data Management with other SAS applications, as I am using SAS Viya, SAS 9.4, and SAS Enterprise Guide. The data query functionality of SAS Data Management is also very useful. Since I am using SAS Data Management, and SAS Data Management is well trusted by all regulatory authorities, the audit trails and security checks are very good. It is very reliable, very time-saving, and the chances of error are minimal.

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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

"The SAS Data Management software has enabled us to have a single source of truth for any data that was earlier being fetched from multiple source systems at multiple times."

"The tool is reliable, quick, and powerful."

"In terms of which features I have found most valuable, I would say the importing and exporting features. Additionally, the data sorting, categorizing and summarizing features, especially how it can summarize based on categories. These are the key features."

"The monitoring capabilities are very good."

"The technical support is excellent."

"I find the solution to be very stable."

"I am impressed with the tool's ability to customize."

"The platform's robust data governance capabilities ensure strong compliance with regulatory standards."

More SAS Data Management 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."

"The most valuable features of Spring Cloud Data Flow are the simple programming model, integration, dependency Injection, and ability to do any injection. Additionally, auto-configuration is another important feature because we don't have to configure the database and or set up the boilerplate in the database in every project. The composability is good, we can create small workloads and compose them in any way we like."

"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."

"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 product is very user-friendly."

"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

Cons

"The solution is very expensive."

"We find we often have to go back and re-train users when there are changes made to the solution because the changes are not intuitive."

"We implemented it a while ago, and we are trying to improve the data delivery performance. We are looking into how to get faster and automated reporting. We would need better designs and workflows."

"For the amount of features that we use, the licensing is expensive."

"The stability could be a bit better. It's lacking in this area right now."

"Very little needs to improve but perhaps a nicer graphic interface and remaining competetive in the growing field of data analytics."

"The support for SAS in Brazil is not the best one, but the support in Sweden is really good, as they visit the company and work to solve the issues."

"SAS Data Management can be improved in terms of the learning curve."

More SAS Data Management cons

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

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

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

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

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

"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."

"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."

"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

Pricing and Cost Advice

"The solution is expensive."

"The tool is a bit expensive."

"The licensing model for vCenter is a perpetual license with yearly payments."

"While it is even free for personal use on the cloud, it can be expensive for desktop installations and enterprise use."

"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."

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

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Comms Service Provider

Construction Company

Government

Financial Services Firm

18%

Computer Software Company

11%

Retailer

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	8
Midsize Enterprise	2
Large Enterprise	8

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

Questions from the Community

What is your experience regarding pricing and costs for SAS Data Management?

From my experience, SAS Data Management is an expensive tool.

See all answers

What needs improvement with SAS Data Management?

SAS Data Management can be improved in terms of the learning curve.

See all answers

What is your primary use case for SAS Data Management?

My main use case for using SAS Data Management is data cleaning for my clinical trial data because my data is very large, and I need clean, reliable, and regulatory compliance data. My data comes f...

See all answers

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...

See all answers

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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Apache Spark Streaming vs Spring Cloud Data Flow

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Product Reports

Buyer's Guide

SAS Data Management

June 2026

Download SAS Data Management product report

Buyer's Guide

Spring Cloud Data Flow

June 2026

Download Spring Cloud Data Flow product report

Also Known As

SAS Data Management Platform, Data Management Platform, DataFlux

No data available

Overview

SAS Data Management provides data integration, governance, and robust reporting tools. It connects to diverse data sources, ensuring quality management and enabling data analysis for technical and non-technical users.

SAS Data Management features flexible data flow creation, scheduling, and ETL control. It enhances data integration and metadata management with tools that support data standardization. Users benefit from its importing and exporting capabilities, connecting to multiple sources. It facilitates improved data quality management and offers a flexible language for diverse needs. Data visualization capabilities further support decision-making across industries, automating reports and data warehouses.

What are the key features of SAS Data Management?

User-friendly interface: Intuitive navigation facilitates ease of use.
Easy data flow creation: Streamlines processes for seamless data management.
Scheduling and ETL control: Automates tasks for increased efficiency.
Data integration: Connects datasets from multiple origins.
Metadata management: Ensures consistency and quality of data.
Data governance: Provides tools for managing data compliance.
Robust reporting: Delivers comprehensive insights through detailed reports.

What benefits and ROI should be considered?

Data standardization: Enhances data predictability and usability.
Data quality management: Improves accuracy and integrity.
Flexible language: Adapts to specific user requirements.
Import/export capabilities: Facilitates seamless data transitions.
Support for diverse users: Offers tools suitable for varied skill levels.
Automation features: Saves time by reducing manual processes.

SAS Data Management helps industries like finance integrate diverse data sources for analytics and reporting. It is used for tasks such as financial reporting, credit risk analysis, and data cleansing. Through user-driven automation, it aids in aligning data warehouses and generating insightful visual outputs, making it ideal for analyzing structured data from sources like Excel and CSV files.

SAS

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

Sample Customers

Data Management, 1-800-FLOWERS.COM, Absa, Aegon, Allianz Global Corporate & SpecialtyAusgrid, Bank of Queensland, Bell, BMC Software, Canada Post, Ceska pojistovna, Chantecler, Chubb Group of Insurance Companies, Credit Guarantee Corporation, Cr_dito y Cauci‹n, Delaware State Police, Deutsche Lufthansa, Directorate of Economics and Statistics, DSM, Enerjisa, ERGO Insurance Group, Florida Department of Corrections, Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare, Livzon Pharmaceutical Group, Los Angeles County, Miami Herald Media Company, Netherlands Enterprise Agency, New Zealand Ministry of Health, Nippon Paper, North Carolina Office of Information Technology Services, Orlando Magic, OTP Group, PITT OHIO, Plano Independent School District, RWE Poland, Spanish Air Force, Stockholm County Council, Telus, The Travel Corporation, Transitions Optical, Triad Analytic Solutions, UNIQA, US Census Bureau, US Department of Housing and Urban Development, USDA National Agricultural Statistics Service, West Midlands Police, XS Inc., Zenith Insurance

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Buyer's Guide

SAS Data Management vs. Spring Cloud Data Flow

June 2026

Free Report: SAS Data Management vs. Spring Cloud Data Flow

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