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Vector database

Zilliz

Fully managed, scalable vector database for enterprise AI applications.

Source rating 5.0 (87) 152k views 152k/mo traffic 0 saves Freemium
Vector database AI Machine Learning
More categories (12)
Milvus Rag Large Language Models Similarity search Cloud database Managed service open-source Data management Scalability High Performance Enterprise AI Cloud computing
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Free + from $0.3 /GB per month

Verdict

A quick read before you dig into the full page.

Best if
You are aI/ML Developers and need: Retrieval Augmented Generation (RAG)
Skip if
You need enterprise SLAs or a fully managed team plan right away
Pick this when
Freemium · Free + from $0.3 /GB per month

Overview

Zilliz provides a fully managed vector database management system, Zilliz Cloud, powered by the open-source Milvus. It is designed for enterprise-grade AI applications, supporting billion-scale vector search, Retrieval Augmented Generation (RAG), and large language models. Zilliz aims to simplify the deployment and scaling of vector search applications by eliminating the need for complex infrastructure management.

Zilliz screenshot

Best for

Short scenarios where Zilliz tends to shine.

  • Retrieval Augmented Generation (RAG)

    Best for AI/ML Developers

  • Recommender System

    Best for Data Scientists

  • Text/Semantic Search

    Best for Enterprise AI Application Builders

  • Image Similarity Search

    Best for Engineers working with Large Language Models (LLMs)

  • Audio Similarity Search

    Best for Researchers in AI/ML

  • Video Similarity Search

    Best for Organizations needing scalable vector search solutions

  • AI Agents

    Best for AI/ML Developers

  • Molecular Similarity Search

    Best for AI/ML Developers

Example outputs 1

Sample generations and before/after results for Zilliz.

Zilliz screenshot
Zilliz screenshot

Access & connections

Where you can use Zilliz.

Platforms

Web

Capabilities

What this tool accepts, produces, and is strongest at.

Highlights

  • Fully managed Milvus service
  • Billion-scale vector search
  • High performance (10x faster retrieval with Cardinal search engine)
  • Highly Scalable (up to 500 CUs, 100 billion items)
  • High Availability (99.95% monthly uptime)
  • Security & Governance (SOC2 Type II, ISO27001, RBAC)
  • Built-in Embedding Pipelines
  • Multi-Cloud availability (AWS, Azure, GCP)
Show 4 more
  • AI Integrations
  • Comprehensive data management (migration, import, backup/restore)
  • Observability (metrics, alerts, monitoring)
  • Role-based Access Control

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FAQ 8

What is Zilliz?
Zilliz provides a fully managed vector database management system, Zilliz Cloud, powered by the open-source Milvus. It is designed for enterprise-grade AI applications, supporting billion-scale vector search, Retrieval Augmented Generation (RAG), and large language models. Zilliz aims to simplify the deployment and scaling of vector search applications by eliminating the need for complex infrastructure management.
How to use Zilliz?
To use Zilliz Cloud, users can sign up for a free account, download one of the official SDKs (Python, Java, Go, Node.js), create their first collection, and perform vector similarity searches. For launching applications, users can upgrade to a pay-as-you-go plan. The platform offers intuitive RESTful APIs and user-friendly SDKs for control and data plane operations.
What is a Compute Unit (CU)?
A compute unit (CU) is a group of hardware resources for serving your indexes and search requests. You can simply consider a CU as a fully-managed physical node for deploying search service.
What is a vCU?
A virtual compute unit (vCU) is used to measure the resources consumed by read operations (such as search and query) and write operations (such as insert, upsert, and delete). The read and write costs vary for different vCU usage.
Which type of CU should I pick?
Select the Performance-optimized CU for instant search results and high concurrent traffic for real-time applications. Choose the Capacity-optimized CU if you need to handle large vector datasets while maintaining reliable search speeds. Opt for the Extended-capacity CU if you need to manage massive-scale datasets where optimizing total cost is prioritized over latency.
How many CUs do I need for a given collection?
Performance-optimized CU supports up to 1.5 million 768-dimensional vectors. Capacity-optimized CU supports up to 5 million 768-dimensional vectors. Extended-capacity CU supports up to 20 million 768-dimensional vectors. These estimates are based on vectors with primary keys only; additional scalar fields may reduce capacity.
How can I get Zilliz Cloud discounts?
When you commit to an annual plan, you can get additional credits based on your usage.
How can I request a new cloud region?
To request a new cloud service provider region for Zilliz Cloud, please fill out the form provided on the website.
Zilliz Free + from $0.3 /GB per month
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