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Zilliz is a vector database company providing products for enterprise-grade AI. Founded by the engineers behind Milvus, a popular open-source vector database, the company develops database technologies to help businesses create AI applications. Originally a Chinese-based company, Zilliz moved its headquarters to Silicon Valley in 2022. Zilliz's breakout product was the open-source Milvus vector database. Rather than heavily advertising Milvus, Zilliz promoted it on GitHub and Reddit, targeting specific developers and leveraging word of mouth. Since Milvus, Zilliz has released a cloud-managed vector database service.
Zilliz was founded in 2017 by Charles Xie (CEO). Originally based in China, Zilliz moved its headquarters to Silicon Valley in 2022 to take advantage of the growing demand for efficient processing techniques to power AI applications. The company is now headquartered in Redwood City, California, and retains a site in Shanghai. Zilliz has grown to over one hundred employees.
Founder Charlies Xie invested several million renminbi (RMB) of his personal money to kickstart the company. In August 2017, Zilliz received an angel round investment worth millions of dollars led by Yungqi partners. In January 2018, the company raised $10M in a Series A round led by Morningside Venture Capital with participation by Green Pine Capital Partners, while the angel round investors Yunqi Partners and Eminence Ventures continued to increase their holdings in the company.
In November 2020, Zilliz closed a $43M Series B funding round led by Hillhouse Capital with participation from TrustBridge Capital, Pavillion Capital, and existing investors 5Y Capital (formerly Morningside Venture Capital) and Yunqi Partners. In August 2022, Zilliz announced a further $60M in funding led by Prosperity7 Ventures (a venture fund created by Saudi oil giant Aramco). The round also included previous Chinese backers Pavilion Capital, Hillhouse Capital, 5Y Capital, and Yunqi Capital. This funding was described as an extension to the Series B round rather than a new round.
Milvus is a cloud-native, open-source vector database that powers embedding similarity search and AI applications. The database can store, index, and manage a billion+ embedding vectors generated by deep neural networks and other machine learning (ML) models. Milvus was first released under an open-source license in October 2019. In April 2020, Milvus became an incubation-stage project at the LF AI & Data Foundation, graduating in June 2021.
Milvus consists of a storage layer and a compute layer. To enhance elasticity and flexibility, all components in Milvus are stateless. The system comprises four levels:
- Access layer—comprises a group of stateless proxies and serves as the front layer of the system and endpoint to users.
- Coordinator service—assigns tasks to the worker nodes and functions as the system's brain.
- Worker nodes—executors that follow instructions from the coordinator service and execute user-triggered DML/DDL commands.
- Storage —the backbone of the system responsible for data persistence. It comprises meta storage, log broker, and object storage.
Zilliz Cloud offers a fully managed cloud-native service for Milvus with a wider feature set. Zilliz Cloud was first released in preview on August 3, 2022. Zilliz Cloud features include the following:
- High-performance vector search
- Low latency with high recall
- Multiple vector search indexes
- Various similarity metrics
- Built-in data filtering
- Full data encryption in transit
The company offers a free version of Zilliz Cloud and three pricing plans (standard, enterprise, self-hosted). Pricing is determined by the plan and the number of compute units (CU) used. CU is a group of hardware resources for serving indexes and search requests.
Zilliz is also developing a number of other products:
- GPTCache—an open-source tool designed to improve the efficiency and speed of GPT-based applications by implementing a cache to store the responses generated by language models.
- Towhee—a framework designed to streamline the processing of unstructured data through the use of Large Language Model (LLM) based pipeline orchestration.
- Attu—a vector database admin tool.
- Milvus CLI—a command-line tool that supports database connection, data operations, and import and export of data.
- Feder—a JavaScript tool designed to aid in comprehending embedding vectors.