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Reduce Your Kafka TCO by 90% with AutoMQ

AutoMQ's cloud-native architecture provides significant cost savings in storage, compute, and network compared to Apache Kafka. By utilizing object storage, auto-scaling, and multi-AZ writes, AutoMQ can reduce cluster TCO by up to 90%.
Storage Cost Optimization
Object Storage Utilization:
AutoMQ primarily uses object storage (e.g., AWS S3), which is about 67% cheaper than block storage (e.g., AWS EBS).
Minimal Block Storage Use:
Only a small amount of block storage is used as a buffer, avoiding the high costs associated with extensive use of EBS.
Compute Cost Optimization
Compute Throughput Bandwidth Savings:
AutoMQ does not require replica replication, theoretically reducing host bandwidth consumption.
Compute Auto-Scaling:
AutoMQ adopts a storage-compute separation architecture, allowing for on-demand scaling of compute resources. This avoids the need to provision for peak loads, significantly reducing compute costs.
Cross-AZ Data Traffic Savings
S3WAL and Multi-Point Writes:
AutoMQ supports S3WAL and multi-point writes, completely eliminating the cross-AZ traffic transmission costs associated with Apache Kafka's replica replication and producer writes.
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Additional Resources

Performance Testing Report

This report provides comparative data on throughput performance and E2E latency of AutoMQ and Apache Kafka in scenarios such as hot message read/write, cold read consumption, and Fanout.
Learn More

TCO Cost Analysis Report

The report compares AutoMQ and Apache Kafka in terms of storage service, computing resources, and cross-availability zone data transfer. AutoMQ can reduce costs by over 90% compared to Apache Kafka.
Learn More

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