Aiven Platform vs Apache Spark Streaming comparison

Aiven and Apache are both solutions in the Streaming Analytics category. Aiven is ranked #13 with an average rating of 8.5, while Apache is ranked #10 with an average rating of 8.2. Aiven holds a 1.3% mindshare in SA, compared to Apache’s 2.7% mindshare. Additionally, 100% of Aiven users are willing to recommend the solution, compared to 91% of Apache users who would recommend it.

Aiven Platform

Read 2 Aiven Platform reviews

1,034 Views
427 Comparison Views

100% willing to recommend

Apache Spark Streaming

Read 11 Apache Spark Streaming reviews

1,689 Views
1,207 Comparison Views

91% willing to recommend

Aiven Platform

Apache Spark Streaming

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Executive Summary

We performed a comparison between Aiven Platform and Apache Spark Streaming 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.

To learn more, read our detailed Streaming Analytics Report (Updated: March 2025).

Buyer's Guide

Streaming Analytics

March 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

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

Apache Spark Streaming

Ranking in Streaming Analytics

10th

Average Rating

8.0

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 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 Apache Spark Streaming is 2.7%, down from 3.8% 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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AbhishekGupta

Engineering Leader at Walmart

Easy integration, beneficial auto-scaling, and good open-sourced support community

The service structure of Apache Spark Streaming can improve. There are a lot of issues with memory management and latency. There is no real-time analytics. We recommend it for the use cases where there is a five-second latency, but not for a millisecond, an IOT-based, or the detection anomaly-based. Flink as a service is much better. Apache Spark Streaming does not have auto-tuning. A customer needs to invest a lot, in terms of management and maintenance.

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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

"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."

"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."

"The solution is very stable and reliable."

"Apache Spark's capabilities for machine learning are quite extensive and can be used in a low-code way."

"Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows."

"Spark Streaming is critical, quite stable, full-featured, and scalable."

"Apache Spark Streaming has features like checkpointing and Streaming API that are useful."

"As an open-source solution, using it is basically free."

"It's the fastest solution on the market with low latency data on data transformations."

"The platform’s most valuable feature for processing real-time data is its ability to handle continuous data streams."

More Apache Spark Streaming pros

Cons

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

"The initial setup is quite complex."

"It was resource-intensive, even for small-scale applications."

"The cost and load-related optimizations are areas where the tool lacks and needs improvement."

"There could be an improvement in the area of the user configuration section, it should be less developer-focused and more business user-focused."

"In terms of improvement, the UI could be better."

"Integrating event-level streaming capabilities could be beneficial."

"We don't have enough experience to be judgmental about its flaws."

"The service structure of Apache Spark Streaming can improve. There are a lot of issues with memory management and latency. There is no real-time analytics. We recommend it for the use cases where there is a five-second latency, but not for a millisecond, an IOT-based, or the detection anomaly-based. Flink as a service is much better."

More Apache Spark Streaming cons

Pricing and Cost Advice

Information not available

"Spark is an affordable solution, especially considering its open-source nature."

"On a scale from one to ten, where one is expensive, or not cost-effective, and ten is cheap, I rate the price a seven."

"People pay for Apache Spark Streaming as a service."

"I was using the open-source community version, which was self-hosted."

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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

27%

Computer Software Company

20%

Manufacturing Company

University

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 do you like most about Apache Spark Streaming?

Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows.

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What needs improvement with Apache Spark Streaming?

We don't have enough experience to be judgmental about its flaws, as we've only used stable features like batch micro-batch. Integration poses no problem; however, I don't use some features and can...

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What is your primary use case for Apache Spark Streaming?

We use Spark Streaming in a micro-batch region. It's not a full real-time system, but it offers high performance and low latency.

See all answers

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Product Reports

Buyer's Guide

Streaming Analytics

March 2025

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Buyer's Guide

Streaming Analytics

March 2025

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Also Known As

No data available

Spark Streaming

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

Spark Streaming makes it easy to build scalable fault-tolerant streaming applications.

Apache

Sample Customers

Information Not Available

UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, eBay Inc.

Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Microsoft and others in Streaming Analytics. Updated: March 2025.

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