Overview

AutoMQ employs a storage-computation separation approach, evolving Apache Kafka from a Shared Nothing architecture to a Shared Storage architecture. This evolution fully leverages the technological and cost advantages inherent to cloud-native solutions. Technically, the shared storage architecture offers inherent benefits in addressing operational pain points such as partition migration and automatic scaling. AutoMQ maximizes these advantages through its product capabilities, as detailed in the following table.

Advantage Points	AutoMQ	Apache Kafka
Native support for Kafka protocol	✅ Natively supported, reuses protocol layer code	✅ Natively supported
Second-level partition migration	✅ Shared storage allows for migration without data replication	❌ Local data migration, typically takes hours per partition
Second-level smooth scaling	✅ Supports rapid scaling through batch partition migration	❌ Scaling is slow due to data replication required for partition migration, typically taking tens of hours
Continuous data rebalancing	✅ Includes an Auto Balancing component for real-time traffic allocation and hotspot elimination	❌ Prone to local hotspots, affecting stability
Stateless Brokers	✅ Data offloaded to shared storage, enabling stateless brokers and the use of Spot instances	❌ Local disk state, decommissioning requires large-scale data transfers
Cold and Hot Data Isolation, 5x Cold Read Efficiency	✅ Out-of-the-box cold and hot data isolation capability, supporting multi-tenant business scenarios	❌ Cold and hot data affect each other, exacerbating system degradation and failing to support multi-tenant scenarios