Fundraising Fox

Zilliz

Redwood City, US · Founded 2017 · 148 employees on LinkedIn · 6 known investors

Find your way into Zilliz

323 people in our graph share verified history with the Zilliz team — schools, employers, funds. One of them is your warm intro.

Howardunlockedknows Charles Xie · together at Cisco (overlapped)
×8knows the team · via Oracle
×3knows the team · via Cisco

Zilliz provides Zilliz Cloud, a managed vector database and "vector lakebase" built by the creators of Milvus, offering real-time serving, iterative discovery, and batch analytics on a single data source at large scale. It supports vector, text, JSON, and geospatial data with hybrid retrieval, filtering, and reranking for enterprises building AI and retrieval-augmented generation applications.

Also known as Zilliz Cloud

Founders & leadership

Zilliz was founded in 2017 by Charles Xie.

CXCharles Xie
Charles XieinFounder · CEOHe created Milvus, an open-source vector database widely used for AI and search applications.

Investors · 6

Also in the syndicate · 3

5Y CapitalTemasek’s Pavilion CapitalYunqi Capital

Funding

SEC filings, press & company announcements

$60M disclosed across 1 of 2 rounds · 2022

Source: company announcements and press reports — follow each round's link for the claim.

Company profile

researched Aug 2026

Zilliz is a data infrastructure company built by the creators of the open-source Milvus vector database. Its commercial offering, positioned as a "Vector Lakebase," combines real-time vector serving, iterative discovery and batch analytics over a single source of truth, with the company stating support for scales of 100 billion-plus entities and more than 10,000 queries per second at consistent latency.

The platform provides full-spectrum search across vector, text, JSON and geospatial data, with hybrid retrieval, metadata filtering and reranking, including BM25 full-text search that can be combined with vector search. Real-time serving is organized into tiers — performance-optimized, capacity-optimized and tiered-storage — alongside massive multi-tenancy with unlimited namespaces, hot/cold data serving, and global multi-region clusters with replication and failover. An on-demand compute mode charges per query rather than per provisioned capacity, supports online backfill and schema evolution without disrupting serving, and includes an optional access mode that builds and serves indexes on Zilliz while customer data remains in their own S3 buckets in Iceberg, Lance, Vortex or Parquet formats. A command-line interface is offered for management, search and analytics, and an interactive "Zilliz Agent" guides product selection on the company site.

Business model

Zilliz sells its Milvus-based vector database as a managed cloud service, with a free entry tier, a fully managed SaaS deployment, and a bring-your-own-cloud (BYOC) option in which customer data remains inside the customer VPC while Zilliz operates the system. Milvus itself remains available as open source for self-hosted deployment, and Zilliz provides migration paths from lake data, Milvus, Elasticsearch and other vector databases.

Consumption-based pricing tied to compute and storage, including compute-unit-based serving tiers and an on-demand search mode billed per query; the site cites illustrative figures of $9.9 per 1,000 searches and $53.7 per month to store 1 billion vectors plus index.

Traction

The company reports production use across more than 10,000 enterprises over eight years and publishes customer testimonials from Exa (entity search), a company serving hundreds of thousands of clinicians, and a multilingual RAG deployment.

Latest developments

Zilliz announced the public preview of its Vector Lakebase, a fully managed, Milvus-powered service unifying real-time vector search, lake-scale discovery and AI data operations, and released an official CLI for management, search and analytics.

Full profile — market position, technology, go-to-market, geography

Market position

Zilliz positions its Vector Lakebase as going "beyond vector databases" by combining serving, discovery and analytics workloads on one data source, and cites production use across more than 10,000 enterprises over eight years.

Stated differentiators include separation of storage and compute with all data and indexes on S3, per-query on-demand search pricing instead of provisioned serverless capacity, the Vortex-based open lake-native format, the ability to serve indexes over data left in the customer's own bucket without ETL or copies, online schema iteration and backfill, and unlimited namespaces for multi-tenant AI applications.

Technology

The system is powered by Milvus and stores all data and indexes on object storage (S3), using a hot cache and on-demand compute that the company says cuts costs by up to 90%. Lake-native storage is built on Vortex, an open columnar format that Zilliz describes as offering up to 10x faster and cheaper random reads than Lance with per-column format flexibility, and unifies storage for both serving and analytics. Query capabilities span dense vector search, BM25 full-text search, JSON and geospatial filtering, hybrid retrieval and reranking.

Go-to-market

Self-service entry via a free tier, CLI installation and demo bookings on the website, complemented by an enterprise motion around BYOC deployments, migration assistance and customer case studies. The open-source Milvus project serves as a top-of-funnel channel to the managed service.

Enterprises and engineering teams building AI applications that require vector retrieval, including retrieval-augmented generation, entity search and multilingual RAG systems; the site references customers with high-QPS, low-latency workloads as well as very large, low-traffic vector corpora.

Geography

Zilliz operates globally distributed infrastructure across AWS, Google Cloud and Azure regions, with multi-region cluster deployment for low-latency, high-availability access.

Compiled by commissioned research from 1 cited public sources — announcements, filings, and press listed under research sources below.

Key figures

latest reported
Benchmarked query performance (performance-optimized tier, 768-dim vectors, top-Jan 20251,476 QPS
Enterprises servedJan 202510,000 enterprises
On-demand search cost (1B 768-dim vectors, top-k=100k, 64 CU)Jan 2025$9.9
Stated maximum scaleJan 2025100B+ entities and 10K+ QPS

Company-reported or press-reported figures, each dated to when it was claimed — not independently audited.

Timeline · 1

launches, deals, and filings
Jan 2025
Zilliz Vector Lakebase enters public preview

Zilliz announced the public preview of its Vector Lakebase, a fully managed offering powered by Milvus that unifies real-time vector search, lake-scale discovery and AI data operations.

source ↗

Dated company events from announcements, filings, and press; legal rows summarize public dockets and regulator releases.

In the news

Research sources · 1

primary sources listed

1 public sources were cited for this profile; the first-party ones are listed here.

Frequently asked questions

What does Zilliz do?
Zilliz offers a managed vector lakebase built on Milvus for real-time vector search, discovery and batch analytics.
Who founded Zilliz?
Zilliz was founded by Charles Xie in 2017.
Who are Zilliz's investors?
Zilliz's investors include Beyond Ventures, Prosperity7 Ventures, Hillhouse Capital.
How much funding has Zilliz raised?
Zilliz has disclosed $60M raised across 1 of its 2 known rounds.
Where is Zilliz headquartered?
Zilliz is headquartered in Redwood City, US.