Serverless Kafka =
Auto Scaling + Auto Savings + Auto Operations

AutoMQ Kafka vs Apache Kafka

Apache Kafka
AutoMQ Kafka
Built-in elasticity strategy
Minute-level continuous traffic rebalancing
Manual operations and maintenance scaling
Hour-level manual traffic rebalancing
Shared storage, partition migration without data replication
Second-level completion of migration switching
Local storage, partition migration requiring data replication
Single partition generally requires minute-level migration time
Using S3 object storage
Pay-as-you-go, pay as needed
Using local disk
Reserve specifications, not flexible
Data offloading to cloud, stateless Broker
Spot instance used for cost reduction
Stateful Broker, data transfer needed for offline
Spot instance not applicable
Three-copy replication across Availability Zones
Direct storage to S3, saving 2/3 of computing nodes and replication traffic
10x cost advantage compared to Apache Kafka
Leveraging cloud-native architecture with services like object storage and Spot instances for high availability and elasticity, it offers customers a 10x cost reduction compared to Apache Kafka.
Second-level partition migration and automatic traffic rebalancing
With storage and state offloaded to the cloud provider's object storage, creating a stateless business logic layer, AutoMQ Kafka cluster achieves second-level partition migration and traffic balancing, effectively overcoming Apache Kafka's challenges with slow scaling and complex migration.
Highly autonomous, mitigating stability risks
Leveraging the full potential of cloud-native capabilities, the system becomes highly autonomous through automatic scaling, automatic traffic balancing, and automatic fault recovery, fundamentally sidestepping stability risks.
100% compatible with Apache Kafka
AutoMQ Kafka chose a minimal storage replacement aspect at the base level, using Kafka's native computation layer, coupled with shared stream storage, effortlessly achieving 100% compatibility with Apache Kafka.
Automated cloud bill analysis and optimization for efficient cloud usage
AutoMQ offers real-time cloud billing analysis and Spot instance integration, aiding users in optimizing cloud resource usage for cost-effective and efficient cloud utilization.
Abundant autoscaling strategies, moving away from manual administration
Leveraging second-level partition migration and traffic auto-balancing, the system integrates scheduled and adaptive elasticity strategies. Simple configurations can handle sudden and regular traffic fluctuations, achieving near-optimal resource utilization.

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Open Source Edition
Tested for open source developers, self-deployment scenarios
Free forever
100% compatibility with Apache Kafka
Second-level partition migration
Automatic traffic rebalancing
Minute-level smooth expansion and contraction
Single copy, high availability
Fully usage-based storage
Community service support
Standard Edition
Provides fully managed service for a large-scale production environments
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Includes all features of the open source edition
Object storage multi-region disaster recovery/Block storage disaster recovery/Multi-cloud disaster recovery
Traffic adaptive tracking/Cron timing elastic policy support
Large-scale Spot Instance/Cloud Bill Automatic Optimization
Out-of-the-box console/Smooth migration of clusters support
Event/Metrics/Operation and Maintenance API integration
Metrics market/Monitoring alarms
SSO/LDAP/AD integrated authentication
Enterprise work orders, expert escort service