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Go Diskless with AutoMQ
AutoMQ is deployed as a stateless, auto-scaling broker with zero local disks to manage.
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Build Applications with AutoMQ
Build elastic applications and microservices with AutoMQ. Create, process, and analyze streams of events with Kafka's strong correctness and durability guarantees. Powerful, native APIs support Kafka Streams, ksqlDB, and Confluent's Parallel Consumer.
Cloud-Native Storage
Leverage S3-compatible object storage for unlimited scalability and 90% cost reduction
Instant Scaling
Scale compute and storage independently in seconds without data migration
Zero Disk Management
Completely diskless architecture eliminates disk management overhead
Pay-as-you-go
Only pay for actual storage used, no over-provisioning required
Scale Kafka with Ease, Pay per GiB
Simplify scaling and costs. AutoMQ eliminates fixed clusters and provisions resources dynamically, charging you solely based on actual network egress.
Built-in Elasticity
AutoMQ automatically adjusts capacity based on demand, preventing over-provisioning and cutting expense.
Auto-Scaling
Scale automatically based on traffic without manual intervention.
Pay-as-You-Go Pricing
Pay only for actual network egress. No idle capacity charges.
Zero Capacity Planning
No capacity planning needed. Adapts to workload in real-time.
90% Cost Reduction
Up to 90% savings by eliminating over-provisioning.
See Auto-Scaling in Action
Watch how AutoMQ automatically adjusts capacity in real-time to match traffic patterns
Automatic Scaling
Instances spin up and down automatically based on real-time traffic
Pay Only for What You Use
No more paying for idle capacity during low-traffic hours
Zero Downtime
Seamless scaling without interrupting your data streams
AutoMQ: The Better Kafka
A complete reimagining of Kafka for the cloud—radically simpler, more cost-effective, and truly elastic.
Superior Performance
- •75% lower write latency with P99 < 50ms
- •5x faster catch-up reads
- •Seconds not hours for partition reassignment
- •Independent produce/consume paths prevent backpressure
Cost Efficiency
- •Up to 10x lower cost than Apache Kafka
- •Pay only for what you use with serverless architecture
- •Automatic tiering to object storage
- •No overprovisioning required
True Elasticity
- •Scale up and down in seconds
- •Auto-scaling based on workload
- •Zero downtime during scaling operations
- •Decouple compute and storage for flexibility
Fully Kafka Compatible
- •100% compatible with Apache Kafka APIs
- •Drop-in replacement for existing applications
- •Works with all Kafka ecosystem tools
- •No code changes required
Cloud Native
- •Built for AWS, Azure, and Google Cloud
- •Leverage cloud object storage (S3, Azure Blob)
- •Multi-AZ deployment by default
- •Integrated with cloud-native tooling
Simple Operations
- •No complex cluster management
- •Automated failover and recovery
- •Built-in monitoring and observability
- •Reduce operational overhead by 90%
Streaming Lakehouses
Natively integrates Iceberg/Delta Lake table formats to auto-convert Kafka topics into query-ready tables without ETL pipelines.
Kafka Linking
Seamlessly replicate data and metadata between AutoMQ and any Kafka protocol-compatible system for hybrid cloud, disaster recovery, and migration.
Kafka Connector
300+ connectors with 100% compatibility with Kafka upstream and downstream ecosystem.
Kafka Cluster Federation
Unified access point for multiple clusters with transparent topic cluster switching through proxy metadata routing for disaster recovery capabilities.
Unified Streaming and Analytics
AutoMQ's Table Topic feature seamlessly bridges streaming and batch analytics. By natively supporting Apache Iceberg and Delta Lake formats, your Kafka topics automatically become queryable tables. Eliminate complex ETL pipelines and data duplication while maintaining real-time data freshness for analytics workloads.
Learn About Table TopicPerformance Comparison
AutoMQ outperforms Apache Kafka on latency, throughput, and rebalancing—by a lot. Looking for a specific metric? Contact us.
| Metric | Apache Kafka® | AutoMQ | |
|---|---|---|---|
| Produce Latency(Median) | 5 ms | AWS 1 AZ: 2 ms AWS Multi-AZ: 5 ms Azure, GCP: 10 ms | |
| Produce Latency(P99) | 100 ms (with Pagecache thrashing) | AWS 1 AZ: 10 ms AWS Multi-AZ: 20 ms Azure, GCP: 30 ms | AutoMQ bypasses both OS PageCache and the Java heap, eliminating GC pauses entirely for consistently low latency. |
| Catch-up Read Throughput | Limited by broker disk I/O | > 1 GB/s per Broker | Data is streamed directly from cloud storage, enabling massive parallel read throughput unbounded by local disk. |
| Maximum Partitions | ~100,000 | ~100,000 | AutoMQ builds on Kafka's KRaft for metadata storage, delivering the same high partition limits as native Apache Kafka. |
| Partition Rebalance Time | Several Hours | Seconds (Near-instant) | Scaling operations require only metadata updates to reassign connections, with zero inter-broker data movement. |
Flexible Architecture for Any Deployment
AutoMQ BYOC
Bring Your Own Cloud
FullyManaged, Shared Responsibility
IaaS resources owned by Customer
Data stays within customer's VPC, ensuring privacy and security
Pay-as-you-go
AWS/GCP/Azure/... +Multi-Cloud Native
AutoMQ Software
Deploy on any cloud or private data center
Self-Hosted and maintenance
Highly customizable and scalable
Suitable for public clouds as well as self-built storage stacks like Ceph/MinIO
Commercial licensing and technical support available
Trusted by Industry Leaders
See what our customers say about AutoMQ
"AutoMQ reduced our Kafka costs by 85% while improving performance. The elastic scaling is truly game-changing."