Zilliz Cloud, o banco de dados vetorial mais performático, construído em Milvus®

Um banco de dados vetorial e serviços de dados totalmente gerenciados, capacitando você a liberar todo o potencial de dados não estruturados para suas aplicações de IA.

Comece Grátis

Assine no AWS, GCP ou Azure Marketplace

Busca com IA Superior

Estratégias de busca otimizadas e zero ajuste manual com AutoIndex acionado por IA e Motor de Busca Cardinal

Optimized Milvus

Alto Desempenho e Escala

Um banco de dados nativo da nuvem com arquitetura distribuída para escalabilidade sob demanda e crescimento econômico

Built for Production Workloads

Construa mais rápido com um conjunto abrangente de recursos de banco de dados vetorial

  • Busca Vetorial de Alto Desempenho

    Busca Vetorial de Alto Desempenho

    Armazene, indexe e gerencie enormes vetores de embedding gerados por redes neurais profundas e outros modelos de machine learning (ML).

  • Baixa Latência com Alto Recall

    Baixa Latência com Alto Recall

    Tenha confiança em seus dados com baixa latência e alto recall, garantindo tomadas de decisão confiáveis e precisas em tempo real.

  • Busca Híbrida

    Busca Híbrida

    Permita consultas em múltiplos campos vetoriais, suportando combinações multimodais, esparsas-densas e densas-texto para resultados mais precisos.

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  • Várias Métricas de Similaridade

    Várias Métricas de Similaridade

    Escolha a métrica de similaridade correta (Cosseno, Euclidiana, IP, etc) para melhorar o desempenho de classificação e clustering.

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  • Consistência Ajustável

    Consistência Ajustável

    Ganhe flexibilidade com múltiplos níveis de consistência para alinhar precisão de dados e desempenho com as necessidades únicas da sua aplicação.

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  • Escale Conforme Necessário

    Escale Conforme Necessário

    Escale horizontalmente sem esforço com arquitetura baseada em componentes, garantindo desempenho máximo e eficiência, independente de flutuações na carga de trabalho.

Comece Grátis

Reduza TCO com Busca Vetorial Nativa na Nuvem

Enquanto o Milvus oferece capacidades poderosas de busca vetorial, ele requer investimento significativo em engenheiros qualificados, ajuste de desempenho e manutenção contínua.

O Zilliz elimina esses custos através do nosso inovador motor de busca Cardinal e ferramentas de gerenciamento — reduzindo o custo total de propriedade em até 70% e otimizado para seus casos de uso: Sistemas de Recomendação, Aplicações RAG ou Sistemas de Detecção de Anomalias.

Construído para Recomendações de Alto Desempenho

Nossa plataforma entrega o alto recall e tempos de resposta rápidos que seus sistemas de recomendação precisam, enquanto reduz custos através de:

  • Indexação consciente de dados e otimizações de hardware reduzem custos de armazenamento e computação sem sacrificar desempenho de busca

  • APIs simplificadas, implantação automatizada e recursos integrados eliminam meses de desenvolvimento e ajuste manual normalmente necessários para implementação de busca vetorial

  • Atualizações, escalonamento e monitoramento automatizados garantem confiabilidade do sistema enquanto eliminam manutenção operacional

Sistema de Recomendação

TCO de 2 anos: Milvus vs. Zilliz Cloud

  • Assinatura Zilliz

  • Operações

  • Desenvolvimento

  • Infraestrutura

Construído para Recomendações de Alto Desempenho

Construa Aplicações de IA com suas Ferramentas Favoritas

Veja o que nossos clientes estão dizendo

“

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

“

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 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

“

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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“

Reliability, 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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“

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

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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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“

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

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“

We 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

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“

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

“

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.

Learn more

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Oferecendo múltiplos níveis e tipos de computação, nossos preços escaláveis e pay-as-you-go cabem em qualquer orçamento e acomodam todos os tipos de cargas de trabalho

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