Zilliz Cloud
Zilliz Cloud is a fully-managed vector database service built on open-source Milvus that provides high-performance similarity search, scalability, and enterprise-grade security across major cloud platforms (AWS, GCP, and Azure).
https://zilliz.com/cloud?ref=aipure
Product Information
Updated:Apr 16, 2025
Zilliz Cloud Monthly Traffic Trends
Zilliz Cloud achieved 150.4K visits with a 5.0% increase in traffic. The introduction of Zilliz Cloud BYOC in February 2025, which allows users to maintain full control of their data within their cloud accounts and VPC, likely contributed to this growth by enhancing security and compliance for regulated industries.
What is Zilliz Cloud
Zilliz Cloud is an enterprise-ready, cloud-native vector database platform designed to store, index, and search billions of embedding vectors for AI applications. Built on top of the popular open-source Milvus database, it offers a comprehensive solution for managing high-dimensional vector data generated by deep neural networks and machine learning models. The platform supports various use cases including semantic search, recommender systems, retrieval augmented generation (RAG), and anomaly detection, making it ideal for organizations looking to implement AI-powered solutions at scale.
Key Features of Zilliz Cloud
Zilliz Cloud is a fully-managed vector database service built on open-source Milvus, designed for high-performance similarity search and vector data management. It offers automated optimization, enterprise-grade security, and seamless scalability across major cloud providers (AWS, GCP, Azure). The platform enables 10x faster vector retrieval compared to other solutions and includes features like hybrid search, dynamic schema support, and comprehensive team access management.
AI-Powered AutoIndex: Automatically optimizes search strategies and performance without manual tuning, using smart query optimizer and Cardinal Search Engine
Hybrid Search Capabilities: Supports simultaneous querying across multiple vector fields, enabling multimodal, sparse-dense, and dense-text combinations for more accurate results
Enterprise-Grade Security: Offers robust security features including private networking, fine-grained access control, and Organizations and Roles management for team collaboration
Scalable Architecture: Provides component-based architecture for horizontal scaling, supporting billions of vectors with on-demand scalability and cost-efficient growth
Use Cases of Zilliz Cloud
AI-Powered Communication: Enables companies like Ivy.ai to scale their GenAI-powered communication systems with fast and accurate vector search capabilities
Image Search and Processing: Helps companies like Picdmo reduce search times from eight seconds to sub-one second for image-based searches and similarity matching
Data Management for Machine Learning: Assists organizations like BOSCH in efficiently processing and searching through large datasets for machine learning applications
Pros
Significantly faster vector retrieval (10x) compared to other solutions
Fully managed service requiring no infrastructure management
Comprehensive feature set with automatic optimization
Flexible pricing options including free tier for testing
Cons
Pricing calculator currently only supports vector data, not scalar data
May require technical expertise to fully utilize advanced features
How to Use Zilliz Cloud
Sign up for Zilliz Cloud: Create a free account at cloud.zilliz.com/signup to get started with Zilliz Cloud
Create a Cluster: Once logged in, create a new cluster through the Zilliz Cloud console. You'll receive cluster credentials that you need to save securely for later connection
Install SDK: Install one of the supported Milvus SDKs (Python, Java, Node.js, etc.) or use the RESTful API to interact with your cluster
Connect to Cluster: Use your cluster credentials (endpoint URL and token/API key) to establish connection to your cluster using the SDK of your choice
Define Schema: Create a collection schema defining the fields and their data types, including vector fields with appropriate index parameters (metric type: COSINE, L2, or IP)
Create Collection: Create a collection based on your schema to store your vector data
Insert Data: Insert your vector data into the collection using the SDK methods. You can insert single entities or batch insert multiple entities
Build Index: Create an index on your vector field to optimize search performance. You can use AUTOINDEX for automatic index selection
Perform Search: Execute vector similarity searches on your data using various search parameters and filters to retrieve relevant results
Monitor & Scale: Monitor your cluster's performance through the console and scale resources up or down as needed based on your workload
Zilliz Cloud FAQs
Zilliz Cloud is a managed vector database built on Milvus® that offers high-performance vector search, AI-powered optimization, and enterprise-grade security. It allows users to store, index, and manage massive embedding vectors generated by deep neural networks and machine learning models.
Official Posts
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Analytics of Zilliz Cloud Website
Zilliz Cloud Traffic & Rankings
177.2K
Monthly Visits
#219439
Global Rank
#3591
Category Rank
Traffic Trends: Oct 2024-Mar 2025
Zilliz Cloud User Insights
00:01:51
Avg. Visit Duration
3.29
Pages Per Visit
48.68%
User Bounce Rate
Top Regions of Zilliz Cloud
US: 19.16%
CN: 12.51%
IN: 6.33%
KR: 3.62%
VN: 3.48%
Others: 54.9%
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