Spring Cloud Data Flow vs Striim comparison

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Spring Cloud Data Flow

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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 in this report how the two Streaming Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Spring Cloud Data Flow vs. Striim Report (Updated: November 2026).

Spring Cloud Data Flow vs. Striim

November 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 Data Integration

33rd

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

27th

Ranking in Streaming Analytics

18th

Average Rating

7.8

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

Cloud Data Integration (17th)

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 Striim is 1.9%, up from 1.0% 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	1.9%
Other	95.5%

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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Neelam Joshi

Senior Analyst at a comms service provider with 5,001-10,000 employees

Real-time replication has transformed data loads but needs clearer logs and better documentation

Striim offers strong capabilities for real-time database replication. Its core strength is low latency, log-based change data capture, which continuously moves the data without putting heavy load on the source systems. It works especially well in Oracle environments and supports more than 150 sources and targets, including Snowflake, Databricks, and Microsoft Fabric, which is hot in the market right now. It handles the initial load and the ongoing CDC in one platform so we do not have to stitch together Kafka or similar processes ourselves. It offers high availability clustering with failovers and can run self-hosted or fully managed on cloud services. The user interface is pretty good and self-explanatory, so there is no issue if a user lands in the application; they do not have to think more. It is self-explanatory, with all the navigation panes clear. However, the only thing is the searchability; if a user has to search which table belongs to which CDC application connection set up on Striim, it is quite extensive and not fruitful from a user interface point of view. Performance-wise, it is quite good; the queues are long, but as I mentioned earlier, the logs are not that self-explanatory that one can understand what exactly is going on behind the scenes.

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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

"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 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 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 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."

"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."

"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."

More Spring Cloud Data Flow pros

"The CDC works nicely by replicating data as changes happen to the source database, running syncs to the target, and applying changes in near-real time."

"Striim's technical support is the best and at par with competitors."

"Striim offers strong capabilities for real-time database replication with low latency, log-based change data capture, which continuously moves the data without putting heavy load on the source systems."

"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."

"Striim's intuitive UI for monitoring, the flow designer, and the real-time console are straightforward and helpful."

"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."

"Striim is definitely my data migration tool and data reflection syncing tool. It reduces manual intervention because it automatically syncs the data from the warehouse."

Cons

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

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

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

"The documentation on offer is not that good."

"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."

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

More Spring Cloud Data Flow cons

"Customer support was non-existent, with some documentation shared by Google personnel but no access to a customer portal for support tickets."

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

"Striim can be improved by providing tools such as short videos or step-by-step manuals to clearly demonstrate its capabilities and help users learn quickly."

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

"I would say Striim performance needs improvement because we use more GoldenGate, so I tend to compare GoldenGate with Striim."

"Pricing is too high compared to other replication tools currently available in the market, especially Fivetran."

"The pricing is a bit on the higher end for Striim."

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

15%

Outsourcing Company

Computer Software Company

Comms Service Provider

Retailer

18%

Construction Company

12%

Healthcare Company

11%

Financial Services Firm

11%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

By reviewers
Company Size	Count
Small Business	2
Large Enterprise	5

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...

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...

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...

What is your experience regarding pricing and costs for Striim?

It's very fair. We had a private cloud, and it's not based on the number of events. It was based on the number of cores and CPU cores.

What needs improvement with Striim?

Striim can be improved by providing tools such as short videos or step-by-step manuals to clearly demonstrate its capabilities and help users learn quickly. Regarding needed improvements, it is imp...

What is your primary use case for Striim?

My main use cases for Striim day-to-day include maintenance, database performance, ensuring data integrity, managing transactional log overload, and simplifying data replication. Zero-downtime clou...

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Product Reports

Download Spring Cloud Data Flow product report

Spring Cloud Data Flow

October 2026

Download Striim product report

October 2026

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.

Sample Customers

Information Not Available

Sky, UPS, MACY'S, EMAAR, HSBC