Industry Leaders Choose AutoMQ
AutoMQ has been adopted by industry leaders in Internet, financial services, automotive manufacturing, and other sectors for production use, replacing Apache Kafka to build a low-cost, auto-scalable data streaming platform.
Hou Zhong
Architect at JD
JD originally used Kafka, but due to the double triple-replication strategy leading to nine times data redundancy, six copies were made. By adopting AutoMQ, which directly relies on the underlying cloud storage CubeFS, the need for upper-layer replication is eliminated. The architecture is expected to save two-thirds of storage costs when fully implemented. AutoMQ's stateless computing layer perfectly meets the requirements for containerization transformation, significantly enhancing system flexibility.
Yihao Zhang
Storage Expert of Red
By leveraging cloud-native architecture and tiered storage, RedKafka accommodates vast amounts of real-time data. However, the challenge lies in flexible scaling and cost optimization. AutoMQ, with its new architecture based on EBS shared storage and object storage, provides significant elasticity improvements for scaling. Its feature of separating storage and computing aligns well with current operational requirements based on Kubernetes. When combined with Red's current messaging engine architecture, it can lead to greater cost savings and efficiency gains.
Tianyu Chen
CTO of GWM
Great Wall Motor is building a multi-cloud, multi-active architecture across multiple public clouds. The challenge lies in achieving cross-cloud, real-time disaster recovery with the message middleware. By choosing AutoMQ, we benefits from its inherent multi-cloud support and Kubernetes compatibility, enabling us to achieve multi-active deployment and traffic orchestration for our multi-cloud applications.
More Customer Cases
JD originally used Kafka, but due to the double triple-replication strategy leading to nine times data redundancy, six copies were made. By adopting AutoMQ, which directly relies on the underlying cloud storage CubeFS, the need for upper-layer replication is eliminated. The architecture is expected to save two-thirds of storage costs when fully implemented. AutoMQ's stateless computing layer perfectly meets the requirements for containerization transformation, significantly enhancing system flexibility.
Hou Zhong
Architect of JD
By leveraging cloud-native architecture and tiered storage, RedKafka accommodates vast amounts of real-time data. However, the challenge lies in flexible scaling and cost optimization. AutoMQ, with its new architecture based on EBS shared storage and object storage, provides significant elasticity improvements for scaling. Its feature of separating storage and computing aligns well with current operational requirements based on Kubernetes. When combined with Red's current messaging engine architecture, it can lead to greater cost savings and efficiency gains.
Yihao Zhang
Storage Expert of Red
Poizon used to rely on Kafka to build the observability platform, requiring a team to spend several days each quarter on scaling operations. Since adopting AutoMQ, data storage has been moved to object storage, making the compute layer stateless and fully compatible with Kafka. This has enabled automatic elastic scaling without manual intervention, significantly reducing cloud resource costs by up to 85%.
Hao
Head of Stability, Poizon
360 extensively adopts Apache Kafka internally. However, its storage-computing integrated architecture requires data migration during scaling, increasing operational burden. In contrast, AutoMQ employs a storage-computing separation architecture, storing data in object storage, eliminating the need for data migration during cluster scaling. Additionally, AutoMQ is fully compatible with Apache Kafka, effectively shielding against hardware failures, ensuring read-write traffic isolation, significantly improving operational efficiency, and reducing scaling risks.
Renyi Wang
Architect of 360
Great Wall Motor is building a multi-cloud, multi-active architecture across multiple public clouds. The challenge lies in achieving cross-cloud, real-time disaster recovery with the message middleware. By choosing AutoMQ, we benefits from its inherent multi-cloud support and Kubernetes compatibility, enabling us to achieve multi-active deployment and traffic orchestration for our multi-cloud applications.
Tianyu Chen
CTO of GWM
TokenPocket is a world-leading crypto wallet, faced the need to replay Kafka messages from years ago. The original Apache Kafka-based solution proved to be costly. By switching to AutoMQ and migrating data storage to object storage, overall costs were significantly reduced.