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Up to 10x Savings Compared to Apache Kafka on the Cloud

AutoMQ is the next generation of cloud-first Kafka. The innovative shared storage architecture allows AutoMQ to significantly reduce the cost of Kafka for customers through technological innovations in multiple dimensions such as computing, storage, and networking.

S3: The Industry Standard for Scalable, Cost-Effective Cloud Storage

The S3 protocol is the de facto standard for cloud object storage. Building modern data infrastructure on mature S3 is now an industry consensus. Compared to traditional local disks or cloud block storage services, S3 offers unlimited capacity, high durability, and a low-cost advantage.

Cost-wise, S3's per GB storage price is just 10% of EBS. With unlimited capacity, AutoMQ doesn't need to pre-reserve local storage capacity like Kafka. This enables AutoMQ to achieve significant storage-level cost reductions compared to Apache Kafka.

AutoMQ is based on an innovative shared storage architecture, where the persistence of data is ensured by the multi-replica mechanism within the dependent cloud storage, rather than relying on Kafka's ISR multi-replica mechanism.

Since the cluster does not need to replicate partition replicas among multiple Brokers like Apache Kafka, it consumes less network bandwidth than Apache Kafka. This means that, with the same network bandwidth of the computing instance, AutoMQ will have a higher throughput limit.

Cloud providers like AWS and GCP charge $0.02 USD/GB for cross-AZ network costs. Utilizing S3's shared storage architecture, AutoMQ avoids all cross-AZ network traffic costs while maintaining full compatibility with Apache Kafka. Within the AutoMQ cluster, partition data migration is eliminated, preventing cross-AZ network traffic costs.

For consumers, AutoMQ's AZ Aware mechanism ensures consumption within the same AZ. For producers, S3's shared storage feature eliminates cross-AZ network costs during data transmission.

Autoscaling Kafka by Workload: Eliminate Over-Provisioning

This not only poses significant operational and maintenance challenges for Apache Kafka but also exacerbates over-provisioning issues. Many cost problems among AutoMQ service customers stem from resource over-provisioning.

Apache Kafka's architecture, which is based on local disk storage and computation integration, makes it difficult to scale up and down. At the same time, every time a new computation node is added, the capacity of computation and storage must also be increased. For instance, in the gaming industry, Kafka clusters must be scaled up in advance for new version releases to handle peak throughput. Throughout testing and production, substantial costs arise from significant resource waste.

Eliminate Data Hotspots and Enhance Cluster Utilization

AutoMQ features a powerful built-in Self-Balancing capability that identifies and manages data hotspots in real-time, ensuring balanced write traffic and QPS across brokers.

This not only eliminates stability risks from Apache Kafka's partition hotspots but also significantly enhances cluster resource utilization, helping customers save resources wasted by low utilization.

Pricing Comparison

Real-world price comparisons with Confluent and Apache Kafka underscore AutoMQ's notable cost reduction benefits.

Comparison with AutoMQ:

Apache Kafka (CNY)
AutoMQ (CNY)
Compute
1017.336
83.896
Storage
1063.695
103.838
Total
2081.061
187.734

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