Embrace the Cloud Native

10x Cost Efficiency with Reinvented Kafka®

Compress your Kafka cloud infra costs by 10x

Transition from hardware dependency to service dependency

Apache Kafka was born in the era of IDC, designed for physical hardware. In the cloud computing era, software defines hardware and provides high availability and reliability with service level agreements. Building Kafka on cloud services eliminates the need to implement complex distributed multi-replica replication protocols, resulting in a simpler architecture and lower costs.

Transform the reservation model to the pay-as-you-go model

Physical server provisioning typically takes months, leading enterprises to budget annually and design software based on reserved resources from a decade ago. However, in today's cloud environment, all resources can be provisioned via API calls. AutoMQ leverages optimal cloud resource selection for cost-effectiveness.
Storage Cost
257.4 USD/Month
2095.7 USD/Month
Computing Cost
201.5 USD/Month
3054.3 USD/Month
Apache Kafka
* The data is tested based on workload ranging from 80MB/s to 1200MB/s.
Cheaper than Apache Kafka
Cheaper than Apache Kafka

Shared storage, no data replication when scaling up

In shared storage architecture, partition data is fully stored in S3, enabling the cluster to scale out without the need for data replication to handle sudden traffic spikes. In contrast, Apache Kafka requires significant bandwidth for data replication after scaling out, limiting its ability to quickly respond to sudden traffic spikes.

Transition from human governance to autonomous Kafka

In the past, software architecture relied on manual stability protection measures to ensure business continuity, such as capacity assessment, stability plans, and traffic throttling. Today, leveraging cloud-native technologies enables automatic scaling, automatic load balancing, and automatic fault recovery, making systems more autonomous and efficient.
Apache Kafka
Traffic surge
Traffic peaks
Business disruption
Traffic surge
Traffic peaks
Business continuity
Sub-second Elasticity

Decouple storage for services, not software

Storage-compute separation is crucial for achieving elasticity. Offloading storage to cloud services significantly reduces operational complexity and enables complete separation of state, leading to a more streamlined architecture. Introducing a distributed storage system would greatly increase operational complexity.

Shared-everything arch is superior to shared-nothing arch

In the past, limitations existed between different hardware types, making Shared Nothing architecture a compromise. However, storage has become highly flexible today, with capacities approaching "infinite". By leveraging shared storage like S3 to achieve storage-compute separation architecture, you can effortlessly perform operations such as partition migration, scaling in/out, in an unprecedentedly simple manner.
Data Rebalancing
1 minute
43 hours
Partition Migration
1.5 s
3 hours
Apache Kafka
* The data is tested based on a write speed of 100MB/s and a retention period of 30 days.
Fully compatible with Apache Kafka

Compatible with the entire compute layer, not just limited to API-level compatibility

The definition of a software product is primarily reflected in the compute layer. Over the past decade, Kafka has released multiple major versions, with the producer message API undergoing dozens of version iterations. To achieve full compatibility, it is necessary to reuse Kafka code as much as possible. Leveraging the native Kafka compute layer and cloud-native streaming storage, AutoMQ achieves 100% compatibility with Kafka functionality by identifying minimal storage replacement entry points.

Ensure compatibility with the latest version of Apache Kafka with at most a one-month lag

By re-implementing the core class kafka.log.LogSegment in Apache Kafka, we have successfully migrated Kafka storage to object storage with minimal changes to other Kafka code. This allows AutoMQ to complete the adaptation within one month of the release of a new version of Apache Kafka, ensuring continuous synchronization with the Kafka community.
Pass 387 compatibility tests
Support all 1000+ KIPs
Compatible with versions 0.9.0 - 3.4.0

Cost White Paper

Product & Deployment
Computing Costs
Storage Costs
Total Costs
AutoMQ Kafka (AWS China Ningxia Region)
2,516 CNY/Month
3,115 CNY/Month
5,631 CNY/Month
Apache Kafka (AWS China Ningxia Region)
30,520 CNY/Month
31,910 CNY/Month
62,430 CNY/Month
Major cloud vendors (Alibaba Cloud Beijing Region)
25,785 CNY/Month
20,000 CNY/Month
45,785 CNY/Month
32,354 CNY/Month
51,321 CNY/Month
83,675 CNY/Month
*  The data is tested based on workloads ranging from 80MB/s to 1200MB/s. Click to learn more details.

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