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Confluent Cloud vs. Amazon MSK

Future-proofing your Apache Kafka® investment and reducing your total cost of ownership is essential, which is many turn to managed Kafka services . In this in-depth comparison of Confluent Cloud vs Amazon MSK, we'll walk you through how each solution's features, scalability, and technical support stack up.

Founded by the original co-creators of Kafka, Confluent delivers a complete data streaming platform that lets you stream, connect, govern, and process your data wherever it lives, on-premises and across multiple clouds. Kora, our cloud-native Kafka engine, has been re-architected to power a seamless, fully managed experience on Confluent Cloud, one that's ready support all of your data streaming projects from inception to large scale.

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Value for Investment
Plan
Cloud-Native
Self-Managed
Custom/Unsupported

Service

Confluent Cloud

Amazon MSK

MSK Serverless

Sizing

Throughput-based

  • Eliminate cumbersome performance testing and reduce infrastructure costs with elastically scalable, scale-to-zero clusters where you only pay for usage versus provisioned infrastructure

Broker-based

  • Allocate time and resources to run performance tests to pick broker types and count
  • Overprovision infrastructure to reduce the need for complex expansions later due to autoscaling limitations (four operations per day)

Throughput-based

  • Elastically scale with support up to 200MBps in and 400MBps out

Confluent Cloud

Throughput-based

  • Eliminate cumbersome performance testing and reduce infrastructure costs with elastically scalable, scale-to-zero clusters where you only pay for usage versus provisioned infrastructure

Amazon MSK

Broker-based

  • Allocate time and resources to run performance tests to pick broker types and count
  • Overprovision infrastructure to reduce the need for complex expansions later due to autoscaling limitations (four operations per day)

MSK Serverless

Throughput-based

  • Elastically scale with support up to 200MBps in and 400MBps out
Deploy
Cloud-Native
Self-Managed
Custom/Unsupported

Service

Confluent Cloud

Amazon MSK

MSK Serverless

Provision

Self-serve, on-demand

  • Provision Kafka clusters along with any other Confluent Cloud component including Schema Registry, Connect & Flink

Self-serve, on-demand for Kafka only

  • Provision Kafka clusters along with Glue Schema Registry and Flink
  • Custom efforts needed for connectors and Kafka proxy

Self-serve, on-demand for Kafka only

  • Provision Kafka clusters along with Glue Schema Registry and Flink
  • Custom efforts needed for connectors and Kafka proxy
Infrastructure as Code

For both control plane and data plane

  • Unified experience for deploying and managing Confluent resources across diverse environments. Leverage Terraform provider to manage both control plane resources—like Clusters and Schema Registry—and data plane resources, such as Topics and ACLs

For control plane only

  • Terraform is only able to deploy and manage control plane resources. Need to build custom operators and processes to manage data plane resources.

For control plane only

  • Terraform is only able to deploy and manage control plane resources. Need to build custom operators and processes to manage data plane resources.

Confluent Cloud

Self-serve, on-demand

  • Provision Kafka clusters along with any other Confluent Cloud component including Schema Registry, Connect & Flink

For both control plane and data plane

  • Unified experience for deploying and managing Confluent resources across diverse environments. Leverage Terraform provider to manage both control plane resources—like Clusters and Schema Registry—and data plane resources, such as Topics and ACLs

Amazon MSK

Self-serve, on-demand for Kafka only

  • Provision Kafka clusters along with Glue Schema Registry and Flink
  • Custom efforts needed for connectors and Kafka proxy

For control plane only

  • Terraform is only able to deploy and manage control plane resources. Need to build custom operators and processes to manage data plane resources.

MSK Serverless

Self-serve, on-demand for Kafka only

  • Provision Kafka clusters along with Glue Schema Registry and Flink
  • Custom efforts needed for connectors and Kafka proxy

For control plane only

  • Terraform is only able to deploy and manage control plane resources. Need to build custom operators and processes to manage data plane resources.
Operate
Cloud-Native
Self-Managed
Custom/Unsupported

Service

Confluent Cloud

Amazon MSK

MSK Serverless

Infra Monitoring

Proactive monitoring

  • Stay focused on app development with proactive cluster monitoring and maintenance from the Kafka experts
  • Infinite Storage enables unlimited cluster-level storage use cases while reducing risk of disk space-related failures

Manual monitoring

  • Assign resources to monitor broker metrics such as CPU utilization to proactively manage cluster performance
  • Monitor and create alerts for disk space to prevent failures due to storage capacity

Proactive monitoring

  • Stay focused on app development with proactive cluster monitoring and maintenance
  • Infinite Storage enables unlimited cluster-level storage use cases while reducing risk of disk space-related failures
Topic Monitoring

Free, pre-aggregated metrics

  • Access most important metrics pre-aggregated at the topic and cluster level at no additional cost; consume metrics with your third party monitoring service of choice using Metrics API

Topic-level metrics cost extra

  • Pay to consume and manually aggregate per-broker and per-topic level metrics to monitor overall usage

Default monitoring is free

  • Access topic-level metrics for free using CloudWatch console, a separate tool for monitoring multiple AWS products; does not include partition level metrics, or native-integration with popular monitoring tools like Datadog and Dynatrace
Upgrades

Always latest stable version

  • Zero intervention as part of non-disruptive rolling upgrades to latest stable Kafka version that includes strategic patches ahead of scheduled Apache releases

Limited version support

  • Manually trigger upgrades once AWS adds support for it after the scheduled Apache release; MSK only supports a subset of Kafka releases

Limited version support

  • Zero intervention as part of nondisruptive rolling upgrades; MSK only supports a subset of Kafka releases and latest version is unknown and fully abstracted
Software Patches

Proactive fixes

  • Stream confidently and reliably with Kafka experts that proactively address known bugs and vulnerabilities and resolve even the most complicated Kafka issues

Reactive fixes

  • MSK chooses to offer only select versions of Kafka and failures due to Kafka software not covered by MSK uptime SLAs. Embracing a subset of releases forces a reactive approach to fixing vulnerabilities.

Reactive fixes

  • MSK chooses to offer only select versions of Kafka and failures due to Kafka software not covered by MSK uptime SLAs. Embracing a subset of releases forces a reactive approach to fixing vulnerabilities.

Confluent Cloud

Proactive monitoring

  • Stay focused on app development with proactive cluster monitoring and maintenance from the Kafka experts
  • Infinite Storage enables unlimited cluster-level storage use cases while reducing risk of disk space-related failures

Free, pre-aggregated metrics

  • Access most important metrics pre-aggregated at the topic and cluster level at no additional cost; consume metrics with your third party monitoring service of choice using Metrics API

Always latest stable version

  • Zero intervention as part of non-disruptive rolling upgrades to latest stable Kafka version that includes strategic patches ahead of scheduled Apache releases

Proactive fixes

  • Stream confidently and reliably with Kafka experts that proactively address known bugs and vulnerabilities and resolve even the most complicated Kafka issues

Amazon MSK

Manual monitoring

  • Assign resources to monitor broker metrics such as CPU utilization to proactively manage cluster performance
  • Monitor and create alerts for disk space to prevent failures due to storage capacity

Topic-level metrics cost extra

  • Pay to consume and manually aggregate per-broker and per-topic level metrics to monitor overall usage

Limited version support

  • Manually trigger upgrades once AWS adds support for it after the scheduled Apache release; MSK only supports a subset of Kafka releases

Reactive fixes

  • MSK chooses to offer only select versions of Kafka and failures due to Kafka software not covered by MSK uptime SLAs. Embracing a subset of releases forces a reactive approach to fixing vulnerabilities.

MSK Serverless

Proactive monitoring

  • Stay focused on app development with proactive cluster monitoring and maintenance
  • Infinite Storage enables unlimited cluster-level storage use cases while reducing risk of disk space-related failures

Default monitoring is free

  • Access topic-level metrics for free using CloudWatch console, a separate tool for monitoring multiple AWS products; does not include partition level metrics, or native-integration with popular monitoring tools like Datadog and Dynatrace

Limited version support

  • Zero intervention as part of nondisruptive rolling upgrades; MSK only supports a subset of Kafka releases and latest version is unknown and fully abstracted

Reactive fixes

  • MSK chooses to offer only select versions of Kafka and failures due to Kafka software not covered by MSK uptime SLAs. Embracing a subset of releases forces a reactive approach to fixing vulnerabilities.
Scale
Cloud-Native
Self-Managed
Custom/Unsupported

Service

Confluent Cloud

Amazon MSK

MSK Serverless

Cluster Expansions

Elastic scalability

  • Automatic resource allocation to your cluster to manage consumer lag as throughput scales up or down to GBps scale with fully elastic, self-balancing clusters
  • Eliminate cluster compute over-provisioning when increasing topic retention with Infinite Storage

Manual data rebalancing

  • Manual data rebalancing process required using Cruise Control after brokers are added to any cluster
  • Tiered storage available, but still need EBS volumes which can be scaled up to 16TB per broker with a 30 broker limit

Elastic scalability

  • Effortless scaling up and down from 0 to 200 MBps with automatic cluster rebalancing
  • Eliminate cluster compute over-provisioning when increasing topic retention with Infinite Storage
Connectors

Pre-built and fully managed

  • Accelerate integration to modern and legacy services across on-premises and public clouds with a continuously growing portfolio of 120+ connectors available either as fully managed components or as pre-built components covered by Confluent support

Self develop and manage

  • Leverage self-built or community-built connectors without expressed technical support from AWS; only underlying MSK Connect infrastructure is included

Self develop and manage

  • Leverage self-built or community-built connectors without expressed technical support from AWS; only underlying MSK Connect infrastructure is included

Confluent Cloud

Elastic scalability

  • Automatic resource allocation to your cluster to manage consumer lag as throughput scales up or down to GBps scale with fully elastic, self-balancing clusters
  • Eliminate cluster compute over-provisioning when increasing topic retention with Infinite Storage

Pre-built and fully managed

  • Accelerate integration to modern and legacy services across on-premises and public clouds with a continuously growing portfolio of 120+ connectors available either as fully managed components or as pre-built components covered by Confluent support

Amazon MSK

Manual data rebalancing

  • Manual data rebalancing process required using Cruise Control after brokers are added to any cluster
  • Tiered storage available, but still need EBS volumes which can be scaled up to 16TB per broker with a 30 broker limit

Self develop and manage

  • Leverage self-built or community-built connectors without expressed technical support from AWS; only underlying MSK Connect infrastructure is included

MSK Serverless

Elastic scalability

  • Effortless scaling up and down from 0 to 200 MBps with automatic cluster rebalancing
  • Eliminate cluster compute over-provisioning when increasing topic retention with Infinite Storage

Self develop and manage

  • Leverage self-built or community-built connectors without expressed technical support from AWS; only underlying MSK Connect infrastructure is included
Stream Processing and Integration
Cloud-Native
Self-Managed
Custom/Unsupported

Service

Confluent Cloud

Amazon MSK

MSK Serverless

Connectors

Pre-built & fully managed

  • Seamlessly and effortlessly integrate Apache Kafka with modern and legacy services across on-premises and public clouds with a continuously growing portfolio of +120 connectors available either as fully managed components or as pre-built components covered by Confluent support

Custom-built & self-managed

  • Integrate Kafka with your data services with the option to build your own connectors or deploy from a small subset of community developed connectors. Custom built connectors require maintenance and Kafka community connectors are not covered by AWS technical support

Custom-built & self-managed

  • Integrate Kafka with your data services with the option to build your own connectors or deploy from a small subset of community developed connectors. Custom built connectors require maintenance and Kafka community connectors are not covered by AWS technical support
Stream Processing

Fully managed

  • Offers fully managed Flink & ksqDB service. Users simply create a cluster and get started with stream processing using SQL like language. Also supports AWS fully managed Lambda service

Adds complexities

  • Supports Lambda and self-managed ksqlDB
  • Supports Managed Service for Apache Flink (MSF), which is powerful but adds complexities. As users need to configure networking, create MSF Studio notebook, author the job using SQL-like syntax, test the code, package the code, upload to S3, and create a MSF application from the uploaded code.

Adds complexities

  • Supports Lambda but does not support ksqlDB
  • Supports Managed Service for Apache Flink (MSF), which is powerful but adds complexities. As users need to configure networking, create MSF Studio notebook, author the job using SQL-like syntax, test the code, package the code, upload to S3, and create a MSF application from the uploaded code.
No-code stream processing

Fully managed

  • Build streaming data pipelines visually using a point-and-click interface with Stream Designer

Custom-built & self-managed

  • Custom efforts are required to build your own no-code stream processing solution

Custom-built & self-managed

  • Custom efforts are required to build your own no-code stream processing solution

Confluent Cloud

Pre-built & fully managed

  • Seamlessly and effortlessly integrate Apache Kafka with modern and legacy services across on-premises and public clouds with a continuously growing portfolio of +120 connectors available either as fully managed components or as pre-built components covered by Confluent support

Fully managed

  • Offers fully managed Flink & ksqDB service. Users simply create a cluster and get started with stream processing using SQL like language. Also supports AWS fully managed Lambda service

Fully managed

  • Build streaming data pipelines visually using a point-and-click interface with Stream Designer

Amazon MSK

Custom-built & self-managed

  • Integrate Kafka with your data services with the option to build your own connectors or deploy from a small subset of community developed connectors. Custom built connectors require maintenance and Kafka community connectors are not covered by AWS technical support

Adds complexities

  • Supports Lambda and self-managed ksqlDB
  • Supports Managed Service for Apache Flink (MSF), which is powerful but adds complexities. As users need to configure networking, create MSF Studio notebook, author the job using SQL-like syntax, test the code, package the code, upload to S3, and create a MSF application from the uploaded code.

Custom-built & self-managed

  • Custom efforts are required to build your own no-code stream processing solution

MSK Serverless

Custom-built & self-managed

  • Integrate Kafka with your data services with the option to build your own connectors or deploy from a small subset of community developed connectors. Custom built connectors require maintenance and Kafka community connectors are not covered by AWS technical support

Adds complexities

  • Supports Lambda but does not support ksqlDB
  • Supports Managed Service for Apache Flink (MSF), which is powerful but adds complexities. As users need to configure networking, create MSF Studio notebook, author the job using SQL-like syntax, test the code, package the code, upload to S3, and create a MSF application from the uploaded code.

Custom-built & self-managed

  • Custom efforts are required to build your own no-code stream processing solution
Management and Monitoring
Cloud-Native
Self-Managed
Custom/Unsupported

Service

Confluent Cloud

Amazon MSK

MSK Serverless

Kafka UI

Fully managed

  • Provides an intuitive easy to use Kafka UI that allows you to manage Control plane resources (Kafka clusters and Connectors), Data plane resources (topics and ACLs) and monitor your resources from the same UI. It also provides native management for Kafka resources, which is useful for Kafka Gitops

Not available

  • You can use the console to manage control plane resources. No Kafka UI, and thus, you will have to rely on free community tools without support or paid third-party tools to manage Kafka resources. Lack of native topic management makes it difficult to implement GitOps with MSK.

Not available

  • You can use the console to manage control plane resources. No Kafka UI, and thus, you will have to rely on free community tools without support or paid third-party tools to manage Kafka resources. Lack of native topic management makes it difficult to implement GitOps with MSK.
Infrastructure Monitoring

Proactive monitoring

  • Stop thinking about infrastructure with features such as Infinite Storage that decouples compute and storage to reduce disk space related failures in addition to proactive monitoring from the Kafka experts to help you maintain peak cluster performance

DIY monitoring

  • Assign resources to export, aggregate and monitor broker level metrics (which increase your third party monitoring services costs) such as disk space to prevent failures due to storage capacity and CPU utilization to proactively manage cluster performance

Proactive monitoring

  • Stay focused on app development with proactive cluster monitoring and maintenance
  • Infinite Storage enables unlimited cluster-level storage use cases while reducing risk of disk space-related failures
Topic Monitoring

Pre-aggregated and free

  • Access most important metrics pre-aggregated at the topic and cluster level consumable through the cloud UI or create custom dashboards when manually integrating Metrics API with your third party monitoring service of choice

PER_TOPIC cost extra

  • Pay to consume and manually aggregate per-broker and per-topic-per-broker level metrics to monitor overall usage; aggregations will need to be recalculated after events such as scaling when partitions are rebalanced across different brokers

Default monitoring is free

  • Topic level is monitoring is included with no additional cost and available using CloudWatch console. Does not include partition level monitoring or access to the metrics API. Could not be easily integrated with popular monitoring tools like Datadog and New Relic.

Confluent Cloud

Fully managed

  • Provides an intuitive easy to use Kafka UI that allows you to manage Control plane resources (Kafka clusters and Connectors), Data plane resources (topics and ACLs) and monitor your resources from the same UI. It also provides native management for Kafka resources, which is useful for Kafka Gitops

Proactive monitoring

  • Stop thinking about infrastructure with features such as Infinite Storage that decouples compute and storage to reduce disk space related failures in addition to proactive monitoring from the Kafka experts to help you maintain peak cluster performance

Pre-aggregated and free

  • Access most important metrics pre-aggregated at the topic and cluster level consumable through the cloud UI or create custom dashboards when manually integrating Metrics API with your third party monitoring service of choice

Amazon MSK

Not available

  • You can use the console to manage control plane resources. No Kafka UI, and thus, you will have to rely on free community tools without support or paid third-party tools to manage Kafka resources. Lack of native topic management makes it difficult to implement GitOps with MSK.

DIY monitoring

  • Assign resources to export, aggregate and monitor broker level metrics (which increase your third party monitoring services costs) such as disk space to prevent failures due to storage capacity and CPU utilization to proactively manage cluster performance

PER_TOPIC cost extra

  • Pay to consume and manually aggregate per-broker and per-topic-per-broker level metrics to monitor overall usage; aggregations will need to be recalculated after events such as scaling when partitions are rebalanced across different brokers

MSK Serverless

Not available

  • You can use the console to manage control plane resources. No Kafka UI, and thus, you will have to rely on free community tools without support or paid third-party tools to manage Kafka resources. Lack of native topic management makes it difficult to implement GitOps with MSK.

Proactive monitoring

  • Stay focused on app development with proactive cluster monitoring and maintenance
  • Infinite Storage enables unlimited cluster-level storage use cases while reducing risk of disk space-related failures

Default monitoring is free

  • Topic level is monitoring is included with no additional cost and available using CloudWatch console. Does not include partition level monitoring or access to the metrics API. Could not be easily integrated with popular monitoring tools like Datadog and New Relic.
Enterprise Grade Security
Cloud-Native
Self-Managed
Custom/Unsupported

Service

Confluent Cloud

Amazon MSK

MSK Serverless

Authentication

Broad authentication

  • Only allows authenticated clients to access the cluster. Supports SASL/PLAIN and SASL/OAUTHBEARER (in preview) as Authentication mechanisms

Broad authentication

  • Allows authenticated access. Supported SASL/SCRAM, mTLS and IAM as Authentication mechanisms

Limited authentication

  • Only allows authenticated clients to access the cluster. Only supports IAM as authentication mechanism.
Encryption

End-to-end encryption

  • Client-Side Field Level Encryption (early access) on Confluent Cloud adds an extra layer of security by encrypting sensitive data on the client, securing it on both client and server, and maintaining security during data in motion between producers and consumers

Not supported

  • No support for field level encryption

Not supported

  • No support for field level encryption
Vulnerability and Bug Patches

Proactive fixes

  • Kafka experts address bugs and known vulnerabilities as identified and implemented across all clusters once fix is tested and stable in order to maintain the highest service availability

Reactive fixes

  • Software related issues excluded from uptime SLAs as AWS cannot address bugs ahead of Kafka releases. MSK customers have option to manually upgrade clusters, if a newer version is supported, or cluster migration if no path to upgrade available

Reactive fixes

  • Software related issues excluded from uptime SLAs as AWS cannot address bugs ahead of Kafka releases. MSK customers have option to manually upgrade clusters, if a newer version is supported, or cluster migration if no path to upgrade available

Confluent Cloud

Broad authentication

  • Only allows authenticated clients to access the cluster. Supports SASL/PLAIN and SASL/OAUTHBEARER (in preview) as Authentication mechanisms

End-to-end encryption

  • Client-Side Field Level Encryption (early access) on Confluent Cloud adds an extra layer of security by encrypting sensitive data on the client, securing it on both client and server, and maintaining security during data in motion between producers and consumers

Proactive fixes

  • Kafka experts address bugs and known vulnerabilities as identified and implemented across all clusters once fix is tested and stable in order to maintain the highest service availability

Amazon MSK

Broad authentication

  • Allows authenticated access. Supported SASL/SCRAM, mTLS and IAM as Authentication mechanisms

Not supported

  • No support for field level encryption

Reactive fixes

  • Software related issues excluded from uptime SLAs as AWS cannot address bugs ahead of Kafka releases. MSK customers have option to manually upgrade clusters, if a newer version is supported, or cluster migration if no path to upgrade available

MSK Serverless

Limited authentication

  • Only allows authenticated clients to access the cluster. Only supports IAM as authentication mechanism.

Not supported

  • No support for field level encryption

Reactive fixes

  • Software related issues excluded from uptime SLAs as AWS cannot address bugs ahead of Kafka releases. MSK customers have option to manually upgrade clusters, if a newer version is supported, or cluster migration if no path to upgrade available
Data Governance
Cloud-Native
Self-Managed
Custom/Unsupported

Service

Confluent Cloud

Amazon MSK

MSK Serverless

Data Governance

Fully managed

  • Provides a suite of fully managed services that work together to manage the availability, integrity, and security of data used across the organization. Stream Governance is built upon three key strategic pillars: Stream Lineage, Stream Catalog, Stream Quality. Data Quality Rules guarantee high-quality streams.

Not available

  • Does not have lineage or catalog capabilities. Need to rely on free community tools without support or paid third-party tools to provide stream governance.
  • For data quality, MSK and MSK Serverless integrate with Confluent and Glue Schema registry. However, they lack broker-side schema validation that enforces data producers to use schema registry to control schema evolution, Data Quality Rules to validate and constrain individual field values within a data stream, and schema linking that syncs schemas across different environments

Not available

  • Does not have lineage or catalog capabilities. Need to rely on free community tools without support or paid third-party tools to provide stream governance.
  • For data quality, MSK and MSK Serverless integrate with Confluent and Glue Schema registry. However, they lack broker-side schema validation that enforces data producers to use schema registry to control schema evolution, Data Quality Rules to validate and constrain individual field values within a data stream, and schema linking that syncs schemas across different environments

Confluent Cloud

Fully managed

  • Provides a suite of fully managed services that work together to manage the availability, integrity, and security of data used across the organization. Stream Governance is built upon three key strategic pillars: Stream Lineage, Stream Catalog, Stream Quality. Data Quality Rules guarantee high-quality streams.

Amazon MSK

Not available

  • Does not have lineage or catalog capabilities. Need to rely on free community tools without support or paid third-party tools to provide stream governance.
  • For data quality, MSK and MSK Serverless integrate with Confluent and Glue Schema registry. However, they lack broker-side schema validation that enforces data producers to use schema registry to control schema evolution, Data Quality Rules to validate and constrain individual field values within a data stream, and schema linking that syncs schemas across different environments

MSK Serverless

Not available

  • Does not have lineage or catalog capabilities. Need to rely on free community tools without support or paid third-party tools to provide stream governance.
  • For data quality, MSK and MSK Serverless integrate with Confluent and Glue Schema registry. However, they lack broker-side schema validation that enforces data producers to use schema registry to control schema evolution, Data Quality Rules to validate and constrain individual field values within a data stream, and schema linking that syncs schemas across different environments