Head-to-head · Stream Processing Software
Amazon Managed Service for Apache Flink vs Kafka Streams
Amazon Managed Service for Apache Flink leads on 1 check, Kafka Streams on 1, and 2 are even. Who comes out ahead on the 4 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.
Our verdict
- Highest scoreAmazon Managed Service for Apache Flink · 9.3/10
- Free planonly Kafka Streams
- Most featuresAmazon Managed Service for Apache Flink · 3 of 3
Amazon Managed Service for Apache Flink scores higher on our rubric for stream processing software: 9.3 against 8.9 out of 10; our editors rank them #1 and #5.
Kafka Streams offers free plan; Amazon Managed Service for Apache Flink doesn't. On deployment model, Kafka Streams gives you Self-hosted where Amazon Managed Service for Apache Flink offers Cloud. Amazon Managed Service for Apache Flink offers sql processing; Kafka Streams doesn't.
Amazon Managed Service for Apache Flink is the better fit for AWS teams wanting managed Flink. Kafka Streams is the better fit for kafka-native Java and Scala applications.
- Amazon Managed Service for Apache Flink fits best
AWS teams wanting managed Flink
- Kafka Streams fits best
Kafka-native Java and Scala applications
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Side by side
| Feature | Amazon Managed Service for Apache Flink 9.3/10 Visit ↗ | Kafka Streams 8.9/10 Visit ↗ |
|---|---|---|
| At a glance | ||
| Editor score | 9.3 | 8.9 |
| Ranking | #1 in Stream Processing Software | #5 in Stream Processing Software |
| Best for | AWS teams wanting managed Flink | Kafka-native Java and Scala applications |
| Pricing model | Paid | Free |
| Starting price | $0.11/unit usage-based | Free plan |
| Free plan | — | ✓ (best) |
| Free trial | — | — |
| Deployment | Cloud | Self-hosted, Cloud |
| Platforms | Web | Windows, macOS, Linux |
| Support | Docs | Community, Docs |
| Built for | Mid-market, Enterprise | Small business, Mid-market, Enterprise |
| Features Amazon Managed Service for Apache Flink 3/3 · Kafka Streams 2/3 | ||
| SQL processing | ✓ (best) | — |
| Stateful processing | ✓ | ✓ |
| Event-time windows | ✓ | ✓ |
| Specs | ||
| Deployment model | Cloud | Self-hosted |
| Supported languages | Java, Scala, Python, SQL | Java, Scala |
| Source connectors | Not checked yet | Not checked yet |
| Our review | ||
| Pros |
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| Cons |
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| Our verdict | Amazon Managed Service for Apache Flink is a cloud service for building, deploying, and operating real-time stream-processing applications with Apache Flink. It supports Java, Scala, Python, and SQL, making it suitable for AWS teams… Read the review → |
Kafka Streams is an open-source client library for building real-time applications and microservices whose input and output data are stored in Apache Kafka clusters. It is designed for developers and teams creating event-driven services,… Read the review → |
Strengths and trade-offs
Amazon Managed Service for Apache Flink — where it wins
- Automatic scaling based on throughput and processing complexity
- Stateful exactly-once processing with checkpoints and durable snapshots
- Integrations with Kinesis, MSK, S3, DynamoDB, and OpenSearch
Where it doesn't
- No free plan is available
- Usage starts at $0.11 per KPU-hour
- Storage and durable backups are billed separately
Kafka Streams — where it wins
- Stateful transformations, aggregations, joins, and four window types
- Exactly-once processing semantics for Kafka-based applications
- Runs self-hosted or in cloud environments without a separate processing cluster
Where it doesn't
- Core integration scope is centered on Apache Kafka
- No SQL support for stream-processing workflows
- Support is limited to community channels and documentation
- Amazon Managed Service for Apache Flink9.3/10 · Paid
A managed Flink service for AWS teams building stateful real-time data pipelines.
Visit AWSFull verdict → - Kafka Streams8.9/10 · Free plan
A free, Kafka-native stream-processing library for Java and Scala applications.
Visit Kafka StreamsFull verdict →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Last updated · How we research and update







