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Cosdata Documentation

Introduction to Cosdata

Cosdata is a cutting-edge vector database designed to tackle the complex challenges of modern search and retrieval. By combining semantic search capabilities with knowledge graphs and advanced AI technologies, Cosdata delivers a powerful platform for building intelligent data applications.

Open Source: Cosdata is fully open-source and available on GitHub. We welcome contributions and feedback from the community!

Tackling Modern Search Challenges

In today’s data-rich environment, traditional keyword-based search methods are no longer sufficient. Organizations face several key challenges:

  • Data Explosion: Managing and searching through massive amounts of structured and unstructured data
  • Context Understanding: Moving beyond simple keyword matching to understand the meaning behind queries
  • Performance at Scale: Maintaining speed and accuracy as data volumes grow exponentially
  • Integration Complexity: Seamlessly connecting search capabilities with existing ML pipelines

Cosdata addresses these challenges with a next-generation vector database specifically designed for precision, speed, and scalability.

Industry-Leading Performance

Independent benchmarks demonstrate Cosdata’s exceptional performance characteristics:

  • 1,773 Queries Per Second: 43% faster than leading competitors
  • 98.08% Recall@5 Accuracy: With 0.98 precision
  • ~3,000 QPS on 4-core Systems: With optimized configurations

On standard hardware configurations, Cosdata consistently outperforms other vector databases in throughput while maintaining high search accuracy. Our optimized configurations can achieve nearly 3,000 queries per second on modest 4-core systems.

For detailed benchmark information, see our Benchmarks page.

Core Capabilities

Cosdata elevates search precision by leveraging hybrid search techniques that combine:

  • Dense Vector Search: Captures semantic meaning through embeddings
  • Sparse Vector Search: Maintains keyword importance similar to traditional search
  • Knowledge Graph Integration: Provides deeper context by leveraging structured relationships

This hybrid approach delivers more relevant, context-rich results even for complex queries, making Cosdata ideal for powering advanced retrieval augmented generation (RAG) pipelines.

2. Lightning-Fast Performance

When dealing with millions of queries or massive datasets, speed is critical. Cosdata delivers exceptional performance through:

  • HNSW Indexing: Hierarchical Navigable Small World algorithms for efficient indexing of high-dimensional vector data
  • Smart Quantization: Advanced compression techniques that maintain accuracy while reducing storage requirements
  • Parallel Processing: Multi-threading and SIMD instructions for maximized performance

These optimizations ensure that Cosdata can handle high-throughput search operations with minimal latency, even at scale.

3. Streamlined Setup and Integration

Cosdata simplifies deployment and integration with:

  • Auto-configuration: Automatic fine-tuning of search parameters for optimal performance
  • Intuitive APIs: Simple RESTful APIs and client libraries for easy interaction
  • Cost Efficiency: Minimized resource consumption without compromising performance

Key Features

  • Semantic Search: Leverage embedding-based hybrid search to deliver deep semantic analysis
  • Structured Knowledge Graphs: Sophisticated context retrieval through structured knowledge representation
  • Hybrid Search Capabilities: Combine explicit relationship queries with vector similarity search
  • Real-Time Search at Scale: Execute real-time vector search with unmatched scalability
  • ML Pipeline Integration: Seamlessly integrate with your existing machine learning workflows
  • Transactional Guarantees: ACID-compliant operations for data consistency
  • Comprehensive Query Language: Powerful Cos Graph Query Language for complex operations

Use Cases

Cosdata excels in a variety of applications:

Retrieval Augmented Generation (RAG)

Power AI-generated content with contextually relevant data retrieved in real-time, enhancing the accuracy and reliability of large language models.

Healthcare Information Retrieval

Enable doctors to quickly access precise information from vast pools of patient records, research papers, and medical knowledge bases.

E-commerce Product Discovery

Deliver fast, accurate product recommendations that understand customer intent beyond simple keyword matching.

Financial Analysis

Process and analyze complex financial documents, extracting insights and relationships that drive better investment decisions.

Knowledge Management

Create intelligent knowledge bases that understand the semantic relationships between documents and concepts.

Getting Started

Ready to explore Cosdata? Continue to the Installation & Quick Start Guide to set up your environment and see Cosdata in action.

For a deeper dive into Cosdata’s capabilities, explore our API documentation and learn about the Cos Graph Query Language.

Community Resources

  • GitHub Repository: Explore the code, report issues, or contribute at github.com/cosdata/cosdata
  • Discord Community: Join our Discord server to connect with other users, get help, and stay updated on the latest developments
  • Documentation: This comprehensive documentation will help you make the most of Cosdata’s capabilities