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Actian VectorAI DB

Actian VectorAI DB

The portable vector database for AI agents beyond the cloud

Website actian.com
Overview

What it is

Actian VectorAI DB is a portable vector database built for AI beyond the cloud. Developers can store, retrieve, and reason over data locally, delivering low-latency vector search on embedded, edge, on-prem, and hybrid systems - with a 22x QPS advantage over Milvus and Qdrant at 10M vectors. Build once, deploy consistently, without relying on cloud-native infrastructure. Teams maintain full data ownership and predictable behavior across edge, on-prem, hybrid, and cloud environments.

Intent

I need it when

Reduce vector database operational costs and achieve predictable pricing for production AI workloads at scale

VectorAI DB offers capacity-based subscription pricing (not per-query fees) that scales predictably with vector count, not query volume. Self-hosted deployment eliminates cloud egress fees, embedding inference costs, and hidden reindexing charges. At 60–100M queries/month, self-hosting becomes 50–75% cheaper than managed cloud alternatives.

Deploy AI applications (RAG, semantic search, agents) on edge devices, embedded systems, or air-gapped facilities without cloud dependencies

VectorAI DB enables local-first vector search with sub-15ms latency on resource-constrained devices (Raspberry Pi, NVIDIA Jetson, industrial servers). Supports offline operation, syncs when connected, and eliminates network latency that blocks real-time AI applications. Portable architecture runs identically from prototype to production across edge, on-prem, and cloud.

Build HIPAA and GDPR-compliant AI systems that keep sensitive data on-premises without third-party cloud processing

VectorAI DB supports on-premises and air-gapped deployment, ensuring patient/customer data never leaves organizational infrastructure. Meets regulatory requirements for data residency and eliminates third-party processing risks inherent in cloud vector databases. Enables clinical decision support and medical imaging search while maintaining compliance.

Run AI applications across distributed multi-site infrastructure (retail branches, manufacturing plants, research facilities) with consistent performance

VectorAI DB supports hybrid and multi-region deployments with identical architecture across edge, on-prem, and cloud environments. Platform engineers can manage vector search consistently across retail locations, factory floors, and branch offices without environment-specific rewrites or vendor lock-in.

Accelerate AI development from prototype to production without changing database architecture or rewriting code

VectorAI DB provides unified SDKs (Python, JavaScript, C++) and consistent deployment model from local development machines to enterprise infrastructure. Developers build once and deploy everywhere—same codebase runs on Raspberry Pi, on-prem servers, or cloud VMs. Eliminates architectural rework and reduces time-to-production.

Drop

Not a fit when

  • Organization requires cloud-native SaaS vector database with per-query billing and no infrastructure management
  • Use case demands real-time multi-tenant isolation and automatic scaling without capacity planning
  • Team lacks infrastructure expertise for on-premises or edge deployment and maintenance
  • Application requires serverless architecture with zero upfront capacity commitment
  • Workload involves highly variable, unpredictable query patterns that benefit from pure usage-based pricing without minimums
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Pricing

USD0 / monthly View pricing