Zilliz Cloud, la base de datos vectorial más eficiente, construida sobre Milvus®
Un servicio de base de datos vectorial y datos completamente gestionado, que te permite desbloquear todo el potencial de los datos no estructurados para tus aplicaciones de IA.
Empieza GratisSuscríbete en AWS, GCP o Azure Marketplace
Búsqueda Superior con IA
Estrategias de búsqueda óptimas y cero ajuste manual gracias al Motor de Búsqueda Cardinal y AutoIndex potenciado por IA
Optimizador de Consultas Inteligente
La selección automatizada de algoritmos optimiza el rendimiento y la precisión de la búsqueda para cada conjunto de datos
Suite de Optimización
Optimizaciones integrales a través de algoritmos, sistemas y hardware
Alto Rendimiento y Escalabilidad
Una base de datos nativa de la nube con arquitectura distribuida para escalabilidad bajo demanda y crecimiento rentable
Almacenamiento por Niveles
La organización automática de niveles de almacenamiento optimiza el rendimiento y el costo, mejorando el ROI
Seguridad y Fiabilidad Sin Compromiso
Una plataforma lista para la empresa ofrece un rendimiento confiable y seguridad de grado empresarial
Multi-Nube
Despliega tus datos no estructurados en AWS, Azure y Google Cloud alrededor del mundo
Construye más rápido con un conjunto completo de funciones de base de datos vectoriales
Búsqueda Vectorial de Alto Rendimiento
Almacena, indexa y gestiona enormes vectores de incrustación generados por redes neuronales profundas y otros modelos de aprendizaje automático (ML).
Baja Latencia con Alta Recuperación
Infunde confianza en tus datos con baja latencia y alta recuperación, asegurando una toma de decisiones en tiempo real confiable y precisa.
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Búsqueda Híbrida
Permite consultar a través de múltiples campos vectoriales, soportando combinaciones multimodales, dispersas-densas y densas-texto para resultados más precisos.
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Varias Métricas de Similitud
Elige la métrica de similitud correcta (Coseno, Euclidiana, IP, etc.) para mejorar el rendimiento de la clasificación y agrupación.
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Consistencia Ajustable
Obtén flexibilidad con múltiples niveles de consistencia para alinear la precisión de los datos y el rendimiento con las necesidades únicas de tu aplicación.
Escala según sea Necesario
Escala horizontalmente sin esfuerzo con una arquitectura basada en componentes, garantizando un rendimiento máximo y eficiencia, independientemente de las fluctuaciones de carga de trabajo.
Reduzca el TCO con Búsqueda Vectorial Nativa de la Nube
Aunque Milvus ofrece capacidades potentes de búsqueda vectorial, requiere una inversión significativa en ingenieros calificados, ajuste de rendimiento y mantenimiento continuo.
Zilliz elimina estos costos a través de nuestro innovador motor de búsqueda Cardinal y herramientas de gestión—reduciendo el costo total de propiedad hasta en un 70% y optimizado para sus casos de uso: Sistemas de Recomendación, Aplicaciones RAG, o Sistemas de Detección de Anomalías.
Construido para Recomendaciones de Alto Rendimiento
Nuestra plataforma ofrece la alta recuperación y los tiempos de respuesta rápidos que tus sistemas de recomendación necesitan, mientras reduce costos a través de:
La indexación consciente de los datos y las optimizaciones de hardware reducen los costos de almacenamiento y computación sin sacrificar el rendimiento de búsqueda
APIs simplificadas, despliegue automatizado y características integradas eliminan meses de desarrollo y ajuste manual típicamente necesarios para la búsqueda vectorial
Las actualizaciones automatizadas, el escalado y el monitoreo garantizan la confiabilidad del sistema mientras eliminan el mantenimiento operativo
Sistema de Recomendación
TCO de 2 años: Milvus vs. Zilliz Cloud
Suscripción de Zilliz
Operaciones
Desarrollo
Infraestructura
Construye Aplicaciones de IA con tus Herramientas Favoritas
Mira lo que nuestros clientes están diciendo
We were running a multilingual RAG system at scale, indexing all of Wikipedia into tens of millions of high-dimensional vectors. Latency targets were tight. We needed a system that could handle real-time retrieval over millions of knowledge vectors without breaking under load. Zilliz gave us that. It freed up engineering cycles and let us focus on improving reasoning on the model side, not managing infrastructure. That reliability mattered because we were operating at 3,500+ dimensions per vector, across a fast-growing corpus, with sub-300ms latency requirements in production. "
Dr. Pratyush Kumar
Co-Founder of Sarvam
I was benchmarking different vector databases, and Milvus was at the top among all the popular options on the market."
Saumil Patel
the Senior Data Scientist from Ivy.ai
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Zilliz Cloud stood out for us with its comprehensive range of index types, automatically optimizing for the perfect balance between recall and performance. Its robust security and private networking features, combined with the advantage of a fully-managed database, have significantly lightened our operational load, enabling us to concentrate on driving innovation rather than managing backend complexities. "
Ben Kramer
Co-founder & CTO of Monterey AI
When we conducted our first test run (on Zilliz Cloud), the performance improvement was astonishing. Our search time went from eight seconds down to sub one second. We were nearly falling off our chairs with amazement at the speed."
Alex Alexander
Co-founder & CEO of Picdmo Inc.
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Zilliz Cloud perfectly aligns with MindStudio's vision. Its high-performance, secure platform and multi-tenancy simplifies data management and unlocks unprecedented productivity and innovation for our users’ AI applications. "
Sean Thielen
CTO @ MindStudio
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I appreciated using the open standard evaluation benchmarks for machine learning in general; this is also true for vector databases. The ones that Zilliz often publicizes have been beneficial, and the fact that they are open is significant. "
Sam Butler
Director of Machine Learning @ Dopple.AI
Learn moreReliability, scalability, and performance are great. The fact that we can outsource all this kind of administration management and don't have to worry about servers breaking helps us put resources into product development and innovation, which truly differentiates our business. "
Michal Oglodek
CTO of Ivy.ai
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Since transitioning from the open-source Milvus vector database to the fully managed Zilliz Cloud, we’ve experienced significant improvements in business performance. We’ve achieved lower operational costs, increased search speed, a more flexible system architecture, and a more stable user experience. Zilliz Cloud also provides expert support to resolve issues quickly and effectively. Overall, Zilliz Cloud has given us greater convenience and a competitive edge, and we are very pleased and optimistic about this change."
Shengyi Pan
CTO of Shulex
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When we identify a need for specific data, we can often find the required data in our database the same day using text or image search with Milvus. This greatly improves our data processing efficiency and has a positive effect on our business operations."
Mr. Zhang
BOSCH’s principal software engineer
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Zilliz is a very integral part of our workflow. If we just swapped Zilliz Cloud with something else, the kind of loops that we get might not make sense, which means the end composition might not sound very nice or might not be very accurate to the text prompt you had given."
Sangarshanan Veera
Senior Software Engineer at Beatoven.ai
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Zilliz Cloud enabled us to scale search while dramatically reducing our costs. Its hybrid search capabilities helped us achieve higher relevance for both text and image queries."
Celine Lightfoot
CTO of Beni
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Working with Zilliz Cloud has been transformative for our AI agent architecture. The hybrid search capability alone delivered a 40% accuracy improvement, and the scalability means we never worry about performance, even during the highest traffic periods. It's been essential to our continued growth."
Sasidhar Janaki
Senior Software Engineer at Rexera
Learn moreWe were facing latency issues and scaling challenges with our previous solutions. When traffic spiked with millions of customer requests, our self-hosted infrastructure couldn't keep up, and document retrieval was taking too long. "
Sasidhar Janaki
Senior Software Engineer at Rexera
Learn moreWe were running a multilingual RAG system at scale, indexing all of Wikipedia into tens of millions of high-dimensional vectors. Latency targets were tight. We needed a system that could handle real-time retrieval over millions of knowledge vectors without breaking under load. Zilliz gave us that. It freed up engineering cycles and let us focus on improving reasoning on the model side, not managing infrastructure. That reliability mattered because we were operating at 3,500+ dimensions per vector, across a fast-growing corpus, with sub-300ms latency requirements in production. "
Dr. Pratyush Kumar
Co-Founder of Sarvam
I was benchmarking different vector databases, and Milvus was at the top among all the popular options on the market."
Saumil Patel
the Senior Data Scientist from Ivy.ai
Learn moreExplora Nuestros Planes de Precios
Ofreciendo múltiples niveles y tipos de computación, nuestros precios escalables y de pago por uso se ajustan a cualquier presupuesto y acomodan todo tipo de cargas de trabajo
Descubre la mejor relación rendimiento-precio del mercado. Ve ahorros potenciales de hasta un 80% en comparación con otras bases de datos vectoriales
