Calcula el coste de la implementación de VectorAI DB
CPU: mínimo 4
* Precio estimado en función de la configuración. El presupuesto definitivo puede variar.
Pricing
Elige el nivel adecuado para tus cargas de trabajo de IA
Community
La opción más popularGratis para siempre
Gratis
Vector Capacity
5K
Entorno de implementación
Equipos de desarrollo locales
Asistencia
Comunidad
Starter
La opción más popular30 días de prueba gratuita
417 $ al mes
Vector Capacity
1M
Entorno de implementación
Servidores/máquinas virtuales más pequeños
Apoya a «
»
Plata
Growth
Built for Production
1.250 $ al mes
Vector Capacity
5M
Entorno de implementación
Servidores grandes / máquinas virtuales
Apoya a «
»
Plata
Empresa
La opción más popularBuilt for large-scale deployment
Personalizado
Vector Capacity
10M+
Entorno de implementación
de infraestructura empresarial
Asistencia
Plata
Borde
La opción más popularBuilt for embedded devices
Personalizado
Vector Capacity
Custom
Deployment Environment
Devices / Embedded Systems
Asistencia técnica
Personalizado
Los precios mensuales que se muestran se facturan anualmente. ¿Tienes alguna pregunta o necesitas ayuda? Ponte en contacto con nosotros
Implementa VectorAI DB en cualquier lugar
VectorAI DB supports flexible deployment environments, including local development, embedded applications, and enterprise infrastructure.
Las plataformas compatibles son:
- Self-managed cloud.
- Bare metal environments.
- On-prem infrastructure.
- Embedded/edge deployments.
Características por nivel
Scale seamlessly with VectorAI DB.
Community |
Starter |
Growth |
Empresa |
Borde |
|
|---|---|---|---|---|---|
Capacidad vectorial |
Vectores de 5K |
~1 millón de vectores |
~5 millones de vectores |
Más de 10 millones de vectores |
1000 vectores |
Caso de uso principal |
Developer experimentation |
Small AI applications |
Mid-scale AI workloads |
Large production deployments |
Embedded AI |
Support |
Community |
Por determinar |
Por determinar |
Por determinar |
Fabricantes de equipos originales/Empresas |
Implementación |
Local dev machines |
Small servers / VMs |
Large servers / VMs |
Enterprise infrastructure |
Devices / embedded systems |
Sistema operativo |
Linux / Windows / Mac |
Linux / Windows / Mac |
Linux / Windows / Mac |
Linux / Windows / Mac |
Linux |
SDKs |
Python / JavaScript |
Python / JavaScript |
Python / JavaScript |
Python / JavaScript |
C++ |
Arquitectura de la CPU |
x86 / ARM64 |
x86 / ARM64 |
x86 / ARM64 |
x86 / ARM64 |
ARM64 |
Architecture |
Client server |
Client server |
Client server |
Client server |
In-process runtime |
Perseverancia |
Basado en disco |
Basado en disco |
Basado en disco |
Basado en disco |
Device storage |
Modelo de escalado |
Vertical |
Vertical |
Vertical |
Vertical |
A nivel de dispositivo |
Modelo de licencia |
Perpetual (Dev Only) |
Suscripción |
Suscripción |
Enterprise subscription |
Perpetual |
Availability |
Sitio web |
Sitio web |
Sitio web |
Sales |
Sales/OEM channel |
Uso en producción |
No |
Sí |
Sí |
Sí |
Sí |
Redistribución comercial |
No |
Servidor OEM |
Servidor OEM |
Servidor OEM |
Fabricantes de equipos originales (OEM) de sistemas integrados |
Preguntas frecuentes
Yes. Actian VectorAI DB Community Edition is free forever for developers working on small projects, experiments, and prototypes. When you sign up for Community Edition, you also get a 30-day full-featured trial of VectorAI DB that starts immediately and supports up to 1 million vector embeddings. After the trial, Community Edition remains available for free with up to 5,000 vector embeddings on local development machines. For production use, higher capacity, or commercial redistribution, choose a paid plan.
VectorAI DB pricing is primarily based on vector capacity. The pricing calculator above helps estimate the right package based on the number of vectors, embedding dimension, precision, metadata size, and recommended hardware. It also supports license stacking, so teams can scale capacity incrementally by combining license tiers and paying for the storage they need.
Yes. VectorAI DB supports flexible deployment environments, including bare metal, on-prem infrastructure, self-managed cloud, embedded, and edge deployments.
Edge is designed for embedded and edge AI applications that need vector search inside a device, application, or OEM product. Unlike the standard client-server editions, Edge uses an in-process runtime, is built for device-level deployment, supports ARM64 on Linux, and uses an embedded/OEM licensing path. The other paid tiers are client-server deployments for small servers, large servers, VMs, or enterprise infrastructure.
Not Sure Where to Start?
Talk with our team about how organizations are using VectorAI DB to build AI agents, reduce retrieval latency, keep sensitive data local, and deploy AI in environments where cloud databases don’t work. We can help you evaluate architectures, deployment models, and real-world AI use cases.
Book a Personalized Demo
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