Aiven Platform vs Spring Cloud Data Flow comparison

Aiven and VMware are both solutions in the Streaming Analytics category. Aiven is ranked #13 with an average rating of 8.0, while VMware is ranked #9 with an average rating of 7.7. Aiven holds a 1.3% mindshare in SA, compared to VMware’s 4.8% mindshare. Additionally, 100% of Aiven users are willing to recommend the solution, compared to 88% of VMware users who would recommend it.

Aiven Platform

Read 2 Aiven Platform reviews

1,101 Views
468 Comparison Views

100% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

2,241 Views
1,660 Comparison Views

88% willing to recommend

Aiven Platform

Spring Cloud Data Flow

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Executive Summary

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

Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Microsoft and others in Streaming Analytics.

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Buyer's Guide

Streaming Analytics

February 2025

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Helped 842,651 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

Aiven Platform

Ranking in Streaming Analytics

13th

Average Rating

8.6

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Spring Cloud Data Flow

Ranking in Streaming Analytics

9th

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Integration (23rd)

Mindshare comparison

As of March 2025, in the Streaming Analytics category, the mindshare of Aiven Platform is 1.3%, up from 1.2% compared to the previous year. The mindshare of Spring Cloud Data Flow is 4.8%, up from 4.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics

Featured Reviews

njadm

CTO and Co-Founder at PeerSpot

Seamlessly handle database upgrades and minimize downtime disruptions

One of the most valuable features of Aiven Platform is that it handles the upgrades for us seamlessly, saving us time that would be spent on routine upgrades. It also provides reliable backups. The ability to minimize disruption during upgrades is very important since any database downtime would mean system-wide disruptions.

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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

"One of the most valuable features of Aiven Platform is that it handles the upgrades for us seamlessly, saving us time that would be spent on routine upgrades."

"What I like best about the tool is that the process for the services is faster compared to other methods. It's easier to use because Aiven for Apache Kafka handles the maintenance, so we have less to manage. We only use Kafka to manage its connectivity."

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

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

"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 dashboards in Spring Cloud Dataflow are quite valuable."

"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 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 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

"I would really like to see Aiven Platform add a user interface for database backups, as this would eliminate the need for a third-party solution."

"One challenge we face is when we want to update the version, for example, from 3.6 to 3.7. It will spawn new nodes, and then there's rebalancing and syncing from other brokers. There's high CPU usage during this process, so the solution can't be used for a while, causing some downtime in our services. To tackle this challenge, we schedule maintenance updates during low-traffic periods when there's less risk and fewer users use the services."

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

"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."

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

"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."

"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."

Pricing and Cost Advice

Information not available

"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

Computer Software Company

21%

Financial Services Firm

15%

Media Company

Real Estate/Law Firm

Financial Services Firm

25%

Computer Software Company

17%

Manufacturing Company

Retailer

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What needs improvement with Aiven for Apache Kafka?

One challenge we face is when we want to update the version, for example, from 3.6 to 3.7. It will spawn new nodes, and then there's rebalancing and syncing from other brokers. There's high CPU usa...

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What is your primary use case for Aiven for Apache Kafka?

I use Aiven for Apache Kafka to handle services dependent on each other. Instead of API calls, we use it for asynchronous processing of all our services. That's the general way we use it.

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What advice do you have for others considering Aiven for Apache Kafka?

Apache Kafka is really good for streaming data or messaging services. It's comparable to other messaging services. Overall, I'd rate Aiven for Apache Kafka an eight out of ten.

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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...

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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

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Product Reports

Buyer's Guide

Streaming Analytics

February 2025

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Buyer's Guide

Spring Cloud Data Flow

March 2025

Download Spring Cloud Data Flow product report

Overview

Aiven for Apache Kafka is a robust data streaming platform utilized for real-time analytics, event-driven architectures, and message brokering, enhancing data processing across systems. It features scalable operations, excellent data replication, and comprehensive monitoring, significantly improving organizational efficiency and decision-making processes through high-level data management capabilities.

Aiven

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 Databricks, Amazon Web Services (AWS), Microsoft and others in Streaming Analytics. Updated: February 2025.

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