Zilliz

Zilliz is a leading provider of vector database technology, specifically designed for enterprise-grade AI applications. At its core, Zilliz is powered by Milvus, the world's most popular and fastest-growing open-source vector database. Zilliz offers this powerful technology as a fully managed cloud service, Zilliz Cloud, which simplifies the deployment, scaling, and maintenance of complex vector search infrastructure. This allows developers and data scientists to focus on building innovative AI applications rather than managing databases.

The platform is engineered to handle massive volumes of unstructured data—such as text, images, audio, and video—by converting it into high-dimensional numerical representations called vector embeddings. Zilliz excels at performing lightning-fast similarity searches on these embeddings, enabling a new generation of AI-powered features that rely on understanding semantic context and relationships within data.

How to use Zilliz

Getting started with Zilliz Cloud is designed to be straightforward, even for those new to vector databases:

1. Sign Up and Deploy: Create a free account on the Zilliz Cloud platform. No credit card is required to start. You can then deploy your vector database on your preferred cloud provider, including AWS, Google Cloud, or Azure, across various global regions.
2. Connect with SDKs: Zilliz provides official SDKs for popular programming languages like Python, Java, Go, and Node.js. Use these SDKs to easily connect your application to your Zilliz Cloud instance.
3. Create a Collection: Define a schema for your data, specifying fields for your vector embeddings and any associated metadata. Then, create a collection to store your data. Zilliz's optimized AUTOINDEX feature helps balance recall and performance automatically.
4. Insert Data: Convert your unstructured data into vector embeddings using your preferred machine learning models or leverage Zilliz's built-in embedding pipelines. Insert these vectors along with their metadata into your collection.
5. Perform Searches: Execute vector similarity searches (Approximate Nearest Neighbor - ANN) to find the most relevant data for a given query vector. You can also apply metadata filters to refine search results, enabling powerful hybrid search capabilities.
6. Integrate and Scale: Integrate the search results into your AI application, such as a RAG system to feed context to an LLM, or a recommender system to suggest items. As your data and traffic grow, you can easily scale your cluster to handle billions of vectors.

Core Features of Zilliz

• High-Performance Vector Search: Powered by the open-source Milvus engine and enhanced with the Cardinal search engine, Zilliz delivers up to 10x faster vector retrieval speeds compared to standard Milvus.
• Massive Scalability: Engineered for large-scale deployments, Zilliz can effortlessly handle over 100 billion vectors, making it ideal for enterprise-level applications.
• Fully Managed Service: Zilliz Cloud is a fully managed service that abstracts away the complexities of database administration, including setup, scaling, backups, and maintenance.
• Enterprise-Grade Security & Governance: Compliant with SOC 2 Type II and ISO 27001 standards, and supports Role-Based Access Control (RBAC) for robust data protection.
• High Availability: Offers an industry-leading 99.95% monthly uptime SLA, ensuring your applications are always available.
• Multi-Cloud Availability: Deployable on AWS, Azure, and GCP across eight regions worldwide, providing flexibility and global reach.
• Built-in Embedding Pipelines: Streamlines the data-to-vector process, from data preparation and chunking to model selection and transformation.
• Broad AI Integrations: Seamlessly integrates with leading AI models and frameworks like LangChain, LlamaIndex, OpenAI, Cohere, and more.

Use Cases for Zilliz

Zilliz's capabilities are applicable across a wide range of AI-driven scenarios:

• Retrieval-Augmented Generation (RAG): Enhance Large Language Models (LLMs) by providing them with relevant, external data from your knowledge base, reducing hallucinations and improving the accuracy of responses.
• Recommender Systems: Recommend products, articles, or media to users by finding items that are semantically similar to their past behaviors and preferences.
• Semantic & Multimodal Search: Create powerful search engines that can find semantically similar text, visually similar images, or similar audio/video clips from vast collections. It also supports cross-modal queries, such as using text to search for images.
• AI Agents: Serve as the long-term memory for AI agents, enabling them to perform real-time search, ground their knowledge, and make more intelligent decisions.
• Molecular Similarity Search: Accelerate drug discovery and chemical research by searching for molecules with similar substructures.

Advantages of Zilliz

Zilliz stands out in the vector database market for several key reasons:

• Performance and Cost-Effectiveness: It is built for high performance while being priced for scalability, offering an optimized total cost of ownership (TCO).
• Open-Source Foundation: Being built on Milvus, it benefits from a vibrant open-source community, rapid innovation, and proven reliability with over 10,000 enterprise users.
• Ease of Use: The fully managed service allows teams to launch a large-scale vector search service in minutes without requiring deep operational expertise.
• Reliability and Security: With enterprise-grade SLAs and security certifications, Zilliz is a trusted choice for mission-critical applications.

Pricing and Plans

Zilliz offers a flexible pricing structure to accommodate different needs and scales:

• Free Tier: A generous free tier allows users to get started, build prototypes, and test the platform without any financial commitment.
• Pay-as-you-go Plan: Once ready to launch an application, users can upgrade to a usage-based plan, paying only for the resources they consume. This is ideal for startups and applications with variable workloads.
• Dedicated Instances: For larger enterprises with demanding performance and security requirements, Zilliz offers dedicated clusters with guaranteed resources.
• Serverless Option: Zilliz Cloud also provides a serverless option, which can offer up to 50x cost savings by automatically scaling resources up and down based on real-time demand.

The website also features a RAG Cost Calculator to help users estimate the costs of their AI pipelines, from embedding to vector search.