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Milvus, the world most popular open-source vector database (42k+ GitHub stars), now offers an official fully managed service: Zilliz Cloud, built by the original Milvus team. Purpose-built for GenAI embedding workloads and trusted by 10,000+ organizations, Zilliz delivers hybrid search and sub-10 ms latency at billion-vector scale. Enjoy a monthly Free Tier (5GB storage, 2.5M vCUs) or try Serverless/Dedicated free for 30 days, cancel anytime.
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Overview
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Zilliz Cloud architecture
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Milvus now offers an official fully managed cloud service: Zilliz Cloud, built by the original Milvus team, for vector search, semantic search, RAG, and GenAI applications. It provides high-performance vector storage and retrieval with hybrid search (vector + metadata filtering), delivering sub-10 ms latency at billion-vector scale for demanding, production environments. Learn more at: https://zilliz.com/?utm_source=awsmp&utm_medium=webpage
Zilliz Cloud is designed for teams that need to move beyond DIY deployments. With elastic, cloud-native scaling, high throughput, and high performance, users don't need to worry about operational overhead of managing infrastructure, making it easier to run Milvus reliably in production.
Built for real GenAI applications across modern AI stacks, Zilliz Cloud integrates seamlessly with popular frameworks like LangChain, LlamaIndex, and Haystack to power production workflows such as RAG pipelines, semantic search, and knowledge retrieval. It runs natively on major cloud platforms including AWS, GCP, and Azure.
Zilliz Cloud supports production use cases including reverse image and video search, recommendation systems, enterprise semantic search, agentic workflows, and anomaly detection across industries like legal tech, e-commerce, marketplaces, and SaaS. In real deployments, customers run multi-billion-vector indexes with sub-200ms visual search performance, achieve high relevance in text and image queries, and scale conversational AI and agentic services with low latency and cost efficiency.
Zilliz Cloud lowers the total cost of ownership for running Milvus at scale, combining high performance with elastic, pay-as-you-go pricing. It is available in Free, Serverless (PAYG), Dedicated Cluster (PAYG or contract), and BYOC plans. Get started with the monthly Free Tier (5 GB storage, 2.5 M vCUs, up to 5 collections), or try Serverless or Dedicated free for 30 days, cancel anytime. Full pricing details at https://zilliz.com/pricing?utm_source=awsmp&utm_medium=webpage
Highlights
- High Performance & Cost Efficiency: Up to 4x faster than open-source Milvus, with hot-warm-cold tiered storage and a cloud-native, index-optimized architecture that delivers a lower total cost than S3-based vector pipelines, with flexible pay-as-you-go pricing.
- Enterprise Scale & Trust: Built for true billion-scale production, featuring advanced multitenancy with 100K+ collections per cluster, elastic auto-scaling, a 99.95% SLA, global clusters for region-level resilience, and enterprise-grade security with BYOC deployment, SOC 2, ISO 27001, and GDPR compliance.
- Next-Gen AI Data Stack: Go beyond vector search with native hybrid vector, full-text, and metadata filtering, 4x faster full-text search than Elasticsearch, 10x faster filtering via JSON Shredding, integrated reranking, and seamless integration with next-generation multimodal data lakes and the big data ecosystem.
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Dimension | Cost/unit |
|---|---|
Zilliz Cloud Usage (Each unit is 0.1 cent of usage) | $0.001 |
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Zilliz Cloud does not currently offer refunds. Please refer to the Acceptable Use Policy for the refund policy. https://zilliz.com/acceptable-use-policy
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Have questions about purchasing Zilliz Cloud? Please review pricing details at https://zilliz.com/pricing or contact us at https://zilliz.com/contact-sales .
Zilliz support has been continuously praised by customers. Review the SLA at https://zilliz.com/sla for more details. For technical help, please contact support@zilliz.com .
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By Weaviate
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In Software Development
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10
In Embeddings
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In Embeddings, Generative AI, Databases
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Vector Storage Scalability
Supports billion-vector scale with high-performance vector storage and retrieval capabilities
Hybrid Search Mechanism
Enables advanced hybrid search combining vector, metadata, and full-text filtering with sub-10 ms latency
Multi-Framework Integration
Native integration with popular AI frameworks including LangChain, LlamaIndex, and Haystack
Cloud-Native Architecture
Elastic, cloud-native infrastructure with auto-scaling and support for multiple cloud platforms
Advanced Indexing Technology
Implements cloud-native, index-optimized architecture with hot-warm-cold tiered storage optimization
Vector Database
Low-latency vector database supporting multimodal media types including text and images
Search Capabilities
Advanced vector similarity search, hybrid search, and filtered search functionality
AI Model Integration
Supports optional integrations with multiple AI platforms including SageMaker, Bedrock, OpenAI, Cohere, and HuggingFace
Cloud Architecture
Fault-tolerant, cloud-native database architecture with multi-language client-side programming support
Search Optimization
Seamless combination of vector search with structured filtering for enhanced data retrieval
Vector Search Capability
Advanced vector search library with distributed infrastructure for high-performance search operations
Filtering Mechanism
Supports advanced filtering capabilities with live index updates and keyword boosting for hybrid search
Scalability Architecture
Fully managed vector database infrastructure designed to handle search and retrieval at any scale
Security Compliance
Enterprise-grade security with SOC 2 Type II and HIPAA certification for data protection
AI Application Integration
Optimized for AI search, recommender systems, and Retrieval Augmented Generation (RAG) applications
Standard contract
No
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Customer reviews
Mihai B.
Exceptional Support and Scalability for Vector Similarity Search
Reviewed on Nov 15, 2025
Review provided by G2
What do you like best about the product?
Profesional technical support, great documentation and the most scalable and reliable solution for vector similarity search
What do you dislike about the product?
Nothing to dislike. Everything is going great so far
What problems is the product solving and how is that benefiting you?
Zilliz addresses the challenge of searching through embeddings created from social media creators' content on a large scale. It effectively manages the complexity involved in handling and retrieving relevant information from vast amounts of such data.
Computer Software
Stable Performance and Excellent Support from Zilliz
Reviewed on Nov 13, 2025
Review provided by G2
What do you like best about the product?
Zilliz has been pretty stable in the last year. The team was very helpful resolving issue in the initial integration period. We currently store about 50 million vectors.
What do you dislike about the product?
The cost can be somewhat high when we stored like 1 billion vectors.
What problems is the product solving and how is that benefiting you?
We use Zilliz as our RAG
Issa M.
Fast, Affordable, and Effortless to Use
Reviewed on Nov 13, 2025
Review provided by G2
What do you like best about the product?
This product is quick, affordable, straightforward, and gets the job done. It's user-friendly and can easily scale to meet growing needs.
What do you dislike about the product?
Modifying collection schemas involves a migration process, which can be quite complex and often takes a significant amount of time to manage.
What problems is the product solving and how is that benefiting you?
Zilliz serves as the primary knowledge base for our AI agent. It drives the RAG functionality for a customer support and shopping assistant AI agent that currently assists millions of e-commerce shoppers.
Computer Software
Fast and Capable Vector Database
Reviewed on Nov 09, 2025
Review provided by G2
What do you like best about the product?
Extremely fast, low-latency vector search, even at a massive scale. The cloud platform is intuitive, and the SDKs (like PyMilvus) are straightforward to integrate.
What do you dislike about the product?
The pricing for the cloud service can be a bit high for smaller projects or individual developers.
What problems is the product solving and how is that benefiting you?
We use Zilliz to power our recommendation system. It solves the critical problem of storing and searching millions of image embeddings at high speed. This benefits us by enabling real-time, accurate visual recommendations and 'similar item' search for our users, which significantly improves user engagement.
伟 .
Lightning-Fast Retrieval with Robust Support
Reviewed on Nov 05, 2025
Review provided by G2
What do you like best about the product?
I truly love using Zilliz for building our video retrieval tool as it has greatly enhanced our ability to convert each frame of a video into vectors and store them effectively in Zilliz Cloud. This functionality allows for accurate and efficient searches for corresponding images or videos, whether making searches from text to images or vice versa. The support from Zilliz is impeccable, with a very active community and extremely reliable database systems, which gives us a great deal of confidence. The most impressive aspect is the retrieval speed; it is exceptionally fast, allowing us to search through millions of vectors in just 200 milliseconds, which is critical for our operations. Additionally, the ability of Zilliz to handle a large capacity of data further boosts its value, making our data management and retrieval processes smooth and efficient.
What do you dislike about the product?
I think the number of vector columns supported in a single collection is a bit low, it seems to be 4 or 8. We would like to be able to search across more dimensions.
What problems is the product solving and how is that benefiting you?
I use Zilliz to convert video frames into vectors stored in Zilliz Cloud, facilitating accurate image or video retrieval. The retrieval speed is extremely fast, processing millions of vectors in 200 milliseconds, and the capacity is very large.