SAS Data Integration Server vs Spring Cloud Data Flow comparison

SAS and VMware are both solutions in the Data Integration category. SAS is ranked #37 with an average rating of 7.5, while VMware is ranked #22 with an average rating of 7.8. SAS holds a 0.5% mindshare in DI, compared to VMware’s 1.1% mindshare. Additionally, 83% of SAS users are willing to recommend the solution, compared to 88% of VMware users who would recommend it.

SAS Data Integration Server

Read 4 SAS Data Integration Server reviews

596 Views
511 Comparison Views

83% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

1,374 Views
1,033 Comparison Views

88% willing to recommend

SAS Data Integration Server

Spring Cloud Data Flow

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Executive SummaryUpdated on Dec 19, 2024

SAS Data Integration Server and Spring Cloud Data Flow are key players in the data integration market. SAS Data Integration Server has an edge in pricing and customer support, while Spring Cloud Data Flow stands out for its comprehensive features and flexibility.

Features: SAS Data Integration Server supports powerful data management and ETL capabilities, seamless integration with diverse data sources, and robust data governance options. Spring Cloud Data Flow features a microservices-based architecture, real-time stream processing, and multi-cloud platform deployment, which enhance its flexibility and scalability.

Ease of Deployment and Customer Service: SAS Data Integration Server employs a traditional deployment model that requires significant initial setup but has strong customer service support. Spring Cloud Data Flow utilizes an agile deployment approach, leveraging cloud services to simplify setup processes, though it relies on community support for assistance.

Pricing and ROI: SAS Data Integration Server involves a higher upfront investment but offers strong ROI through its comprehensive services and support. Spring Cloud Data Flow, with its lower initial costs and open-source roots, provides attractive ROI for businesses focusing on scalable, cost-effective data processing, balancing initial support costs with long-term flexibility benefits.

To learn more, read our detailed SAS Data Integration Server vs. Spring Cloud Data Flow Report (Updated: April 2025).

Buyer's Guide

SAS Data Integration Server vs. Spring Cloud Data Flow

April 2025

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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 Integration Server

Ranking in Data Integration

37th

Average Rating

7.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Spring Cloud Data Flow

Ranking in Data Integration

22nd

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (9th)

Mindshare comparison

As of May 2025, in the Data Integration category, the mindshare of SAS Data Integration Server is 0.5%, up from 0.5% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.1%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

reviewer2937544

Works at a financial services firm with 5,001-10,000 employees

Offloads processes on the server side but needs better installation syntax

One area for improvement is the installation process. Another point could be the syntax, as it sometimes involves using syntax names that are not intuitive. For example, to calculate the difference between two dates, the general syntax in SAS is called the data difference or data net function. However, another name is used, such as NF and INK. Without knowledge of SAS programming, it becomes unclear what these functions mean. It is not good to define function names this way.

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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

"A key feature allows us to enhance job performance by offloading processing to the server side, rather than processing on the server itself."

"The most valuable feature of the solution is its amazing capabilities in regard to data handling."

"A key feature allows us to enhance job performance by offloading processing to the server side, rather than processing on the server itself."

"The solution offers very good data manipulation and loading."

"The solution is very stable."

"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."

"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 feature is real-time streaming."

"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 dashboards in Spring Cloud Dataflow are quite valuable."

"The product is very user-friendly."

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

"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."

Cons

"The initial setup had issues, and even after using it for about one year, it was still not fixed."

"So I would like to see improved integration with other software."

"The initial setup of SAS Data Integration Server was complex."

"The transform tool has limited access. They should make it more flexible."

"One area for improvement is the installation process."

"The initial setup had issues, and even after using it for about one year, it was still not fixed."

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

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

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

"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."

"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 solution's community support could be improved."

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

Pricing and Cost Advice

"It is an expensive program."

"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."

"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

26%

Computer Software Company

14%

Government

12%

Insurance Company

Financial Services Firm

27%

Computer Software Company

17%

Retailer

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about SAS Data Integration Server?

The most valuable feature of the solution is its amazing capabilities in regard to data handling.

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

I don't handle the cost and budget part. From the tool's perspective, I can say that it is an amazing product.

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What needs improvement with SAS Data Integration Server?

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

SSIS vs SAS Data Integration Server

Compared 28% of the time

Azure Data Factory vs SAS Data Integration Server

Compared 25% of the time

Oracle Data Integrator (ODI) vs SAS Data Integration Server

Compared 19% of the time

Palantir Foundry vs SAS Data Integration Server

Compared 16% of the time

AWS Glue vs SAS Data Integration Server

Compared 12% of the time

More SAS Data Integration Server Competitors

Apache Flink vs Spring Cloud Data Flow

Compared 42% of the time

TIBCO BusinessWorks vs Spring Cloud Data Flow

Compared 11% of the time

Google Cloud Dataflow vs Spring Cloud Data Flow

Compared 7% of the time

Apache Spark Streaming vs Spring Cloud Data Flow

Compared 5% of the time

MuleSoft Anypoint Platform vs Spring Cloud Data Flow

Compared 5% of the time

More Spring Cloud Data Flow Competitors

Product Reports

Buyer's Guide

Data Integration

May 2025

Download SAS Data Integration Server product report

Buyer's Guide

Spring Cloud Data Flow

April 2025

Download Spring Cloud Data Flow product report

Also Known As

SAS Enterprise Data Integration Server, Enterprise Data Integration Server

No data available

Overview

SAS Data Integration Server is a powerful, configurable and comprehensive solution that can meet a wide variety of data integration requirements, from small tactical projects to strategic business initiatives. It can access virtually all data sources, support data warehousing, migration, synchronization, federation and provisioning initiatives. It can support both batch-oriented and real-time master data management solutions. It can create reusable data integration services in support of service-oriented architectures and data governance and extract, cleanse, transform, conform, aggregate, load and manage data.

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.

VMware

Sample Customers

Credit Guarantee Corporation, Cr_dito y Cauci‹n, Delaware State Police, Deutsche Lufthansa, Directorate of Economics and Statistics, DSM, Livzon Pharmaceutical Group, Los Angeles County, Miami Herald Media Company, Netherlands Enterprise Agency, New Zealand Ministry of Health, Nippon Paper, West Midlands Police, XS Inc., Zenith Insurance

Information Not Available

Buyer's Guide

SAS Data Integration Server vs. Spring Cloud Data Flow

April 2025

Free Report: SAS Data Integration Server vs. Spring Cloud Data Flow

Find out what your peers are saying about SAS Data Integration Server vs. Spring Cloud Data Flow and other solutions. Updated: April 2025.

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