AutoMQ provides a fully stateless, diskless Kafka service that runs on cloud object storage such as S3, delivering sub‑10 ms P99 latency while eliminating the high storage and cross‑AZ costs of traditional Kafka clusters. It offers 100% Apache Kafka API compatibility and auto‑scales compute resources on demand, with pay‑as‑you‑go pricing and optional BYOC deployment in the customer's own cloud account.
Funding
$13.9M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional Kafka deployments rely on local disks, fixed clusters, and multi‑AZ replication, leading to high storage costs, cross‑AZ network fees, and the need to over‑provision compute for peak loads. Managing scaling, rebalancing, and failover adds significant operational overhead.
Solution
AutoMQ re‑architects Kafka to run on cloud object storage (S3 or compatible services) instead of local disks, delivering a fully stateless, diskless streaming platform. By aggregating writes into a single write‑ahead log object and using an in‑memory dual‑cache for reads, it achieves sub‑10 ms P99 latency while keeping storage costs at S3 rates and eliminating cross‑AZ traffic. Brokers are compute‑only and can scale up or down in seconds based on workload, with automatic partition rebalancing and no data movement. The service is 100 % compatible with Apache Kafka APIs and ecosystem tools, so existing producers, consumers, and connectors work without code changes. AutoMQ is offered as a managed service that can be deployed in the customer’s own cloud account (BYOC) or as a fully managed offering, providing pay‑as‑you‑go pricing tied to actual data transferred.
Target Audience
Primary customers are engineering teams that run large‑scale event streaming workloads—such as data platforms, microservices, real‑time analytics, and fraud detection—across enterprises and SaaS providers seeking lower cost, elastic Kafka infrastructure.
Features
- Stateless broker architecture that decouples compute from storage, enabling instant scaling and zero idle capacity
- S3‑native write‑ahead log with O(1) API cost regardless of partition count, reducing storage spend by up to 21× versus EBS
- Dual‑cache engine: in‑memory WAL cache for hot tailing reads and LRU block cache for cold catch‑up reads, delivering 5× faster cold reads
- Sub‑10 ms P99 end‑to‑end latency for real‑time pipelines using a low‑latency WAL backend (regional EBS/NFS or pure S3)
- Zero cross‑AZ network traffic and replication costs through “stay local, store regional” design
- Automatic auto‑balancer that redistributes partitions instantly without data movement, achieving 300× faster reassignment than Apache Kafka
- Full Apache Kafka API compatibility; drop‑in replacement for producers, consumers, Connect, Streams, and admin tools
- Multi‑cloud deployment (AWS, Azure, GCP, OCI) with VPC‑isolated BYOC option and integrated RBAC/SSO for enterprise security