Zilliz
Zilliz is on a mission to unleash data insights with AI. The company builds next-generation database technologies to help organizations rapidly create AI/ML applications and unlock the potential of unstructured data.
At a Glance
- Enterprise AI and ML application developers
- Technology companies building AI/LLM applications
- E-commerce and retail (product search and recommendations)
- Financial services and fintech
- +10 more
AI Tools by Zilliz
(2)
Zilliz Cloud
Managed Vector Database Service
Milvus
Open Source Vector Database for GenAI
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Latest News
Zilliz Selects AWS as its Strategic Cloud Provider to Power Global Vector Database Solutions
Zilliz Achieves AWS Agentic AI Specialization, Empowering Enterprises to Deploy Autonomous AI Systems at Scale
Zilliz Cloud is Now Available in the New AWS Marketplace AI Agents and Tools Category
Milvus 2.6: Built for Scale, Designed to Reduce Costs
Products & Services
The world's most popular open-source vector database designed to store, index, and manage large-scale embedding vectors for AI applications. Joined LF AI & Data Foundation as a top-level project.
Fully managed vector database service (DBaaS) built on Milvus that simplifies deployment, scaling, and management of vector search applications in the cloud. Available on AWS, GCP, and Azure.
Open-source framework for vector data ETL (Extract, Transform, Load) operations.
Designed for organizations that prioritize custom infrastructure, enhanced data protection, and compliance. Allows deployment on customer's own infrastructure with same features as SaaS Dedicated clusters.
Market Position
Zilliz positions itself as the leading provider of open-source and commercial vector database technologies, built on Milvus, the world's most popular open-source vector database with 33,000+ GitHub stars and 100M+ downloads. Key differentiators include: (1) Open-source foundation ensuring no vendor lock-in, (2) Proven performance winning BigANN challenge at NeurIPS 2021, (3) Multi-cloud support across AWS, GCP, and Azure, (4) Cost-effectiveness with tiered storage options starting at $7 per million vectors, (5) Enterprise-grade features including 99.95% uptime SLA, HIPAA compliance, and CMEK support, (6) Strong academic foundation with publications at SIGMOD and VLDB, (7) Trusted by 10,000+ enterprises including Fortune 500 companies.
Leadership
Founders
Charles Xie
Previously worked as a software engineer at Oracle in the U.S. where he was one of the founding engineers of the Oracle 12c cloud database project. Before that, he was a Software Engineer Intern at Cisco. Charles holds a master's degree in computer science.
Executive Team
Charles Xie
Founder & CEO
Previously founding engineer of Oracle 12c cloud database project. Holds master's degree in computer science. Also known by nickname 'Starlord'.
James Luan
VP Engineering
Board of Directors
Founding Story
Zilliz was founded in 2017 in Shanghai, China by Charles Xie (who goes by the nickname Starlord). The company was built by the engineers who created Milvus, the world's most popular open-source vector database. Zilliz's journey started with the creation of Milvus in 2019, which eventually joined the LF AI & Data Foundation as a top-level project.
Business Model
Revenue Model
SaaS subscription and usage-based pricing for managed cloud services (Zilliz Cloud), with enterprise licenses and support contracts. Revenue generated through API usage, compute units (vCUs), storage, and data transfer. Also offers BYOC (Bring Your Own Cloud) for custom deployments.
Pricing Tiers
Starting point for learning and personal projects. 5 GB storage. 2.5M vCUs per month included. Up to 5 collections.
Managed essentials for non-critical workloads. Best for prototypes and testing environments. Fully managed vector databases with core APIs. Backup, restore, and basic monitoring. Built-in encryption for data in transit and at rest.
Managed essentials for non-critical workloads with dedicated resources.
Enterprise-grade reliability and controls for production applications. 99.95% uptime SLA. Audit logs, SSO (SAML 2.0), granular RBAC. Multi-replica and elastic scaling. Private endpoint and VPC peering. Enterprise support included.
Regulated-ready with maximum resilience for healthcare, finance, and highly regulated systems. Global cluster with high availability and disaster recovery. Advanced security with CMEK and full-path encryption. HIPAA-eligible. Priority support and rapid incident response.
Deploy on your own infrastructure with enhanced data protection and compliance. Same features as SaaS Dedicated clusters.
Ideal for real-time applications. 1.5M vectors per CU. 500-1500 QPS. 10ms latency.
For large vector datasets with reliable speeds. 5M vectors per CU. 100-300 QPS. 50-100ms latency.
Ultra-large-scale, cost-sensitive workloads. 20M 768-dim vectors per query CU. Hot data: 100-150 QPS, 20-40ms latency. Cold data: 5-20 QPS, 200-1000ms latency.
Target Markets
- Enterprise AI and ML application developers
- Technology companies building AI/LLM applications
- E-commerce and retail (product search and recommendations)
- Financial services and fintech
- Healthcare and life sciences
- Legal technology
- Real-time vector search for AI applications
- Similarity search and recommendations
- Image and video search and deduplication
- Semantic search and natural language processing
- Conversational AI and chatbots
- RAG (Retrieval Augmented Generation) for LLMs
- NVIDIA
- PayPal
- AT&T
- Walmart