A lighter self-hosted RAG setup may cut operating burden
Milvus is a strong for RAG, but running it at larger scale can require a heavy setup. In production, Milvus may mean using a distributed setup with Kubernetes, etcd, such as MinIO, and a message queue before the search system is ready to answer requests. That can be difficult for offline environments, edge deployments, or small teams that do not want to manage Kubernetes.
Actian’s benchmark positions VectorAI DB as simpler because it runs in one , has no outside , and does not need internet access. On the same hardware with 1 million vectors and 768 dimensions, VectorAI DB was presented as having higher throughput than Milvus and a 73% faster index load. Milvus still had better recall, with 0.9983 versus 0.9948.
The comparison also needs caution because Milvus was tested in standalone mode, not its distributed setup.
Key points
- Milvus can require Kubernetes and other services for larger production use.
- VectorAI DB is presented as running in a single without internet access.
- The benchmark used 1 million vectors, 768 dimensions, and the same hardware.
- VectorAI DB was shown with higher throughput and faster index loading.
- Milvus kept the lead on recall, so search quality may still favor it.