Spring Cloud Data Flow vs Striim comparison

Broadcom and Striim are both solutions in the Streaming Analytics category. Broadcom is ranked #17 with an average rating of 7.5, while Striim is ranked #23 with an average rating of 8.0. Broadcom holds a 2.6% mindshare in SA, compared to Striim’s 1.7% mindshare. Additionally, 88% of Broadcom users are willing to recommend the solution, compared to 100% of Striim users who would recommend it.

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

4,388 Views
1,448 Comparison Views

88% willing to recommend

Striim

Read 2 Striim reviews

1,932 Views
638 Comparison Views

100% willing to recommend

Spring Cloud Data Flow

Striim

Comparison Buyer's Guide

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Executive Summary

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

Find out what your peers are saying about Databricks, Microsoft, Apache and others in Streaming Analytics.

To learn more, read our detailed Streaming Analytics Report (Updated: July 2026).

Buyer's Guide

Streaming Analytics

July 2026

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Helped 909,153 peers since 2012

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 Data Integration

31st

Ranking in Streaming Analytics

17th

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Striim

Ranking in Data Integration

47th

Ranking in Streaming Analytics

23rd

Average Rating

8.0

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

Cloud Data Integration (27th)

Mindshare comparison

As of August 2026, in the Streaming Analytics category, the mindshare of Spring Cloud Data Flow is 2.6%, down from 4.7% compared to the previous year. The mindshare of Striim is 1.7%, up from 0.6% 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%
Striim	1.7%
Other	95.7%

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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Ramakanth Vanga

Data Engineer

Real-time data capture has accelerated releases and now improves trust in our data warehouse

The checkpoints would help me to figure out where the problem was if there's any lag, but I had to do a lot of manual work to figure out where the lag is. Striim would not intuitively tell me the culprit table or database behind the lag. I believe that is an improvement Striim could definitely do. Passwords were an issue. Property variables were not supported for passwords, meaning I had to make sure the password is manually populated. I believe if Striim could read from AWS secrets or its own secret mechanism to store the password, that would really save a lot of time so that I don't have to keep updating the password whenever there is any change. The user experience of triggering alerts if there's any lag which Striim identified, which is outside normal processing time, could intrinsically be done by Striim. I believe that was lacking. I would wait for Striim to tell me, instead of me going and validating whether Striim is lagging behind. If Striim could itself tell me that it's seeing a lot more volume than expected, that would really make me give it a higher number.

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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 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 most valuable feature is real-time streaming."

"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."

"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."

"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 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."

More Spring Cloud Data Flow pros

"Striim is capable of absorbing a large number of transactions, and the difference between the two databases is always less than a second, which demonstrates efficiency and highlights the variety of sources and targets I have used."

"We were confidently in a situation to call Snowflake as a single source of truth, and I believe with Striim, we were able to do that because without Striim, the SLA would be much higher, and there would not have been much confidence in Snowflake."

Cons

"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."

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

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

"The documentation on offer is not that good."

"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."

"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."

More Spring Cloud Data Flow cons

"The user experience of triggering alerts if there's any lag which Striim identified, which is not normal, could intrinsically be done by Striim."

"I think Striim could be improved with better pricing and enhanced documentation."

Pricing and Cost Advice

"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."

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

10%

Retailer

Outsourcing Company

Construction Company

16%

Healthcare Company

13%

Retailer

12%

Financial Services Firm

10%

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...

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

What is your experience regarding pricing and costs for Striim?

My experience with the pricing, implementation cost, and licensing of Striim is that it is somewhat expensive.

See all answers

What needs improvement with Striim?

I think Striim could be improved with better pricing and enhanced documentation.

See all answers

What is your primary use case for Striim?

I use Striim to perform change data capture from relational databases to non-relational databases in my organization. I implement CDC with Striim by transferring data from Oracle Database to MongoD...

See all answers

Comparisons

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Compared 9% of the time

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Compared 6% of the time

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Compared 6% of the time

TIBCO BusinessWorks 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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Compared 14% of the time

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Compared 10% of the time

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Compared 10% of the time

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Compared 10% of the time

Confluent vs Striim

Compared 9% of the time

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Product Reports

Buyer's Guide

Spring Cloud Data Flow

July 2026

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Buyer's Guide

Streaming Analytics

July 2026

Download Striim product report

Also Known As

No data available

Striim Platform

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

Striim offers a comprehensive platform for real-time data integration and streaming analytics, designed to streamline data processes for enterprise-level solutions.

Striim enables seamless migration and integration of data across cloud and on-premises environments, making it ideal for businesses looking to leverage real-time analytics. Its capabilities support continuous data flow, reducing latency and enhancing decision-making. Designed for scalable and secure data management, Striim facilitates effective data-driven strategies.

What are some key features of Striim?

Continuous Data Ingestion: Collects and processes real-time data streams promptly.
Data Integration: Combines data from different sources for unified insights.
Real-Time Analytics: Supports instant analytics, allowing fast response to changes.
Scalable Architecture: Adapts to large-scale data environments efficiently.

What benefits should users look for in Striim reviews?

Improved Data Accuracy: Ensures data integrity in analytics.
Enhanced Operational Efficiency: Streamlined processes for faster data handling.
Cost-Effective Integration: Reduces expenses associated with traditional data handling.
Flexible Deployment Options: Allows for tailored solutions fitting specific needs.

In industries like finance, Striim supports real-time fraud detection by providing uninterrupted data streaming between transaction systems. In healthcare, it enables rapid data processing for patient monitoring, improving service delivery. Manufacturing uses Striim to enhance supply chain visibility through real-time data analytics.

Striim

Sample Customers

Information Not Available

Sky, UPS, MACY'S, EMAAR, HSBC

Find out what your peers are saying about Databricks, Microsoft, Apache and others in Streaming Analytics. Updated: July 2026.

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