Head-to-head · Event Streaming Platforms
Confluent Cloud vs Amazon Managed Streaming for Apache Kafka
Confluent Cloud leads on 0 checks, Amazon Managed Streaming for Apache Kafka on 0, and 3 are even. Who comes out ahead on the 3 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.
Our verdict
- Highest scoreConfluent Cloud · 9.2/10
- Free planonly Confluent Cloud
- Free trialonly Confluent Cloud
Confluent Cloud scores higher on our rubric for event streaming platforms: 9.2 against 8.8 out of 10; our editors rank them #2 and #5.
Confluent Cloud is the better fit for enterprises needing governed managed Kafka. Amazon Managed Streaming for Apache Kafka is the better fit for AWS teams running managed Apache Kafka.
- Confluent Cloud fits best
Enterprises needing governed managed Kafka
- Amazon Managed Streaming for Apache Kafka fits best
AWS teams running managed Apache Kafka
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Side by side
| Feature | Confluent Cloud 9.2/10 Visit ↗ | Amazon Managed Streaming for Apache Kafka 8.8/10 Visit ↗ |
|---|---|---|
| At a glance | ||
| Editor score | 9.2 | 8.8 |
| Ranking | #2 in Event Streaming Platforms | #5 in Event Streaming Platforms |
| Best for | Enterprises needing governed managed Kafka | AWS teams running managed Apache Kafka |
| Pricing model | Free plan + paid | Paid |
| Starting price | $385/mo | Not checked yet |
| Free plan | ✓ (best) | Not checked yet |
| Free trial | 30 days | — |
| Deployment | Cloud | Cloud |
| Platforms | Web | Web |
| Support | Tickets, Community, Docs · 24/7 | Docs |
| Integrations | 150+ integrations | 17 integrations |
| Built for | Small business, Mid-market, Enterprise | Mid-market, Enterprise |
| Features Confluent Cloud 2/2 · Amazon Managed Streaming for Apache Kafka 2/2 | ||
| Stream processing | ✓ | ✓ |
| Schema registry | ✓ | ✓ |
| Specs | ||
| Deployment model | Cloud | Cloud |
| Maximum retention | Not checked yet | Not checked yet |
| Delivery guarantee | Both | Both |
| Connectors listed | 80 connectors | Not checked yet |
| Supported client languages | Java, Python, Go, JavaScript, .NET, C/C++ | Java, Python, Go, JavaScript, .NET |
| Our review | ||
| Pros |
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| Cons |
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| Our verdict | Confluent Cloud is a cloud service for organizations building real-time data pipelines, event-driven applications, streaming analytics, and data integrations. It provides fully managed Apache Kafka clusters through web and API access, with… Read the review → |
Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a cloud service for developers, data engineers, and DevOps teams building applications that publish, consume, process, and replay streaming data. AWS manages cluster provisioning,… Read the review → |
Strengths and trade-offs
Confluent Cloud — where it wins
- Fully managed Kafka with autoscaling and 80+ connectors
- Schema Registry, Flink processing, governance, and lineage
- TLS, RBAC, ACLs, audit logs, and SAML/SSO controls
Where it doesn't
- Standard starts at $385 per month
- Consumption-based billing varies by usage and cloud region
- Advanced enterprise features require the $895-per-month plan
Amazon Managed Streaming for Apache Kafka — where it wins
- Provisioned and serverless Kafka cluster deployment options
- MSK Connect, cross-cluster replication, and schema registry integration
- IAM access control with broad AWS service integrations
Where it doesn't
- Usage-based pricing varies across multiple infrastructure factors
- AWS-focused integrations may not suit multicloud architectures
- Requires Kafka expertise for configuration and application development
- Confluent Cloud9.2/10 · Free plan · 30-day trial
A broad managed Kafka platform with strong governance, but a high paid entry price.
Try Confluent CloudFull verdict → - Amazon Managed Streaming for Apache Kafka8.8/10 · Paid
A deep AWS-native Kafka service for teams that need managed streaming infrastructure.
Visit Amazon MSKFull verdict →
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All event streaming platforms comparisons → · Full ranking →
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Last updated · How we research and update







