Real-time vector serving
Serve low-latency vector search for production workloads, with tiered options that trade off performance and cost across different dataset sizes and traffic levels.
Zilliz
Freemium
Database vettoriale e piattaforma Vector Lakebase completamente gestite per workload di AI aziendale, con ricerca in tempo reale, recupero ibrido, SaaS e BYOC.
Cos'è Zilliz?
Zilliz is a fully managed vector database and Vector Lakebase platform powered by Milvus. It is designed for enterprise AI workloads that need real-time serving, iterative discovery, and batch analytics across large vector datasets.
The product combines vector search with broader data operations, including hybrid retrieval, full-text search, filtering, reranking, and lake-native storage. The site positions it as a single source of truth for AI data at hundred-billion scale, with deployment options that include SaaS, BYOC, and an open-source Milvus path.
Cosa può fare Zilliz?
Lake-native storage
Store and query data for both serving and analytics on a unified lake-native layer, with the product positioned as a Vector Lakebase built on Vortex.
Full-spectrum search
Use hybrid retrieval across vector, text, JSON, and geospatial data, with filtering and reranking for more expressive queries.
Tiered architecture
Choose between performance-optimized, capacity-optimized, and tiered-storage cluster types to match latency, throughput, and cost requirements.
On-demand compute and indexing
Run on-demand query and indexing jobs on zero-copy external data, so search workloads can operate without always-on compute.
BYOC deployment
Keep data in your own cloud environment with BYOC, where Zilliz manages the control plane while customer data stays in the customer VPC.
Casi d'uso
“Production semantic search”
Build low-latency AI applications that need vector retrieval at production scale, with configuration choices based on traffic, latency, and dataset size.
“Large-scale cost-sensitive retrieval”
Run search over huge datasets where cost matters as much as performance, using tiered storage, on-demand compute, or BYOC to match infrastructure constraints.
“Hybrid retrieval workflows”
Support AI systems that mix vector search with text, JSON, geospatial, and reranked results, rather than treating embeddings as the only query type.
“Private cloud deployments”
Keep sensitive data inside a customer-controlled environment while still using a managed service, which fits teams with compliance or sovereignty requirements.
“Online schema evolution”
Operate continuously changing AI datasets by backfilling and iterating on schema and data models without interrupting serving.
Domande frequenti
What is Zilliz Cloud?
Zilliz Cloud is a fully managed vector database and Vector Lakebase platform powered by Milvus. The source positioning emphasizes real-time serving, iterative discovery, batch analytics, and AI data operations on a single source of truth.
What deployment options are available?
The source material shows deployment options for SaaS on Zilliz Cloud, BYOC in the customer’s own cloud environment, and an open-source Milvus option. The pricing page also lists dedicated, serverless, and BYOC plans.
Does Zilliz offer a free tier or trial?
Pricing is shown for Free, Standard, Enterprise, Business Critical, On-demand Compute, and BYOC. The pricing page includes a free starting point, a 30-day free trial for some paid plans, and a contact-sales flow for higher-touch options.
Does Zilliz support combining vector and text search?
Yes. The source states that Zilliz supports hybrid retrieval and full-spectrum search, including vector search, text, JSON, and geospatial data, plus full-text search and reranking.
Informazioni rapide
- Category
- Vector database / Vector Lakebase
- Primary platform
- Zilliz Cloud powered by Milvus
- Deployment options
- SaaS, BYOC, and open-source Milvus
- Clouds mentioned
- AWS, Google Cloud, Azure
- APIs and SDKs
- RESTful APIs and Python, Java, Go, Node.js SDKs
- Source domain
- zilliz.com
Analisi del traffico di Zilliz
I dati sul traffico sono solo a scopo di riferimento.
- Domain Rating
- 73
