Zilliz is a leading provider of a vector database management system, designed specifically for performance and scalability. Built on the open-source Milvus, Zilliz offers a powerful solution for managing vector data, making it an ideal choice for AI applications at any scale. With a focus on delivering cost-effective services, Zilliz stands out in the competitive landscape of database management systems.
Zilliz is equipped with a range of features that enhance its functionality and user experience:
With the Cardinal search engine, Zilliz enables a vector retrieval speed that is ten times faster than Milvus. This high performance is crucial for applications that require quick access to large datasets.
Zilliz is designed for users of all experience levels. Setting up a large-scale vector similarity search service can be accomplished in just minutes, making it accessible for both beginners and experts.
The platform is built to handle large-scale vector data efficiently. Users can easily scale their clusters to 500 Compute Units (CUs), allowing them to serve over 100 billion items without compromising performance.
Zilliz ensures a reliable customer experience with industry-leading Service Level Agreements (SLAs). The platform boasts a monthly uptime of 99.95% for all products hosted on their cloud.
Data protection is a priority for Zilliz. The platform meets SOC2 Type II and ISO27001 standards, and it supports Role-Based Access Control (RBAC) to safeguard sensitive information.
Zilliz simplifies the process of converting unstructured data into searchable vector embeddings. The built-in pipelines guide users through data preparation, chunking, model selection, and transformation.
Zilliz is accessible on major cloud platforms, including AWS, Azure, and Google Cloud Platform (GCP). This multi-cloud support ensures that users can leverage Zilliz’s capabilities regardless of their preferred hosting environment.
The platform integrates seamlessly with leading AI models and frameworks, transforming unstructured data into valuable searchable assets. This feature enhances the utility of the database for various AI applications.
Zilliz is versatile and can be applied in various scenarios:
This use case allows users to expand the knowledge of Large Language Models (LLMs) by incorporating external data, enhancing the models’ capabilities.
Zilliz can be utilized to search for similar molecular structures, including substructures and superstructures, making it valuable for research and development in the pharmaceutical and chemical industries.
The platform supports querying across different modalities, such as text, video, audio, and images. This feature is particularly useful for applications that require comprehensive data analysis across various formats.
New users can easily begin their journey with Zilliz:
Zilliz offers a free trial that does not require a credit card. Users can sign up for a Zilliz Cloud account and start building their first collection and conducting vector similarity searches within minutes.
Once users are ready to launch their applications, they can upgrade to a pay-as-you-go plan, providing flexibility and cost management as their needs grow.
Zilliz provides a robust and scalable vector database solution that meets the demands of enterprise-grade AI applications. With its powerful features, ease of use, and strong performance, Zilliz is well-positioned to support organizations in managing their vector data effectively.
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