Supercharge Your AI|
Cosdata's next-generation vector database delivers lightning-fast performance at billion-vector scale, powering the AI applications of tomorrow
Our Products
Explore our suite of cutting-edge vector database solutions designed for different use cases and requirements
Cosdata OSS
High-performance vector database with industry-leading query speeds and hybrid search capabilities.
- Market-Leading Benchmarks
- Self-hosted deployment
- Advanced hybrid search
- Knowledge graph integration Coming Soon
Cosdata Serverless
Infinitely scalable vector database with zero operational overhead, powered by our CHANNI technology.
- Zero operational overhead
- Pay-as-you-go pricing
- Adaptive scaling
- Knowledge graph integration Coming Soon
Industry-Leading Performance
Cosdata consistently outperforms competing solutions across both vector and full-text search benchmarks
Dense Vector Search Benchmark Highlights
Our HNSW implementation delivers exceptional performance across all key metrics:
- Industry-leading 1758+ QPS on 1M record datasets with 1536-dimensional vectors
- 42% faster than Qdrant and 54% faster than Weaviate
- Up to 146% faster than ElasticSearch while maintaining high precision
- Consistent 97% precision across challenging search tasks
Full-Text Search Benchmark Highlights
Compared to ElasticSearch across multiple datasets, Cosdata's custom BM25 implementation delivers:
- Up to 16x higher QPS than ElasticSearch on comparable datasets
- Significantly faster indexing, up to 12x faster on large datasets
- Lower latency at both p50 and p95 percentiles across all tested datasets
- Maintains similar recall and NDCG scores while delivering superior performance
Precision Performance, Effortless Integration
Discover how our intuitive and tailored solutions can enhance your data management experience.
Effortless Management
RESTful APIs: Easily manage all database functions through intuitive HTTP interfaces for seamless interaction.
Client SDKs: Quickly integrate with your preferred programming language using SDKs available across multiple platforms.
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Optimized Indexing
Dense Vector Index: Achieve high-efficiency indexing using our optimized HNSW algorithm for precise search results.
Sparse Vector Index: Supporting SPLADE-generated sparse vectors alongside our custom BM25 implementation for comprehensive lexical search capabilities.
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Flexible Hyperparameter Control
Auto-configuration: Automatically fine-tune system parameters with insights-driven setup for optimal performance without manual effort.
Manual Precision: Gain full control by customizing indexing and querying parameters for specialized use cases and performance needs.
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Enterprise-Grade Scalability and Security
Unbounded Scalability
Secure Data Management
Advanced Version Control
Research & Innovation
Our cutting-edge research powers the next generation of vector search technology
CHANNI
Multi-Level Vector Search Index with Nested Graph Navigation
CHANNI introduces a novel vector indexing architecture that bridges the gap between memory-efficient clustering and high-performance graph navigation, combining hierarchical navigable small world graphs at multiple levels.
Key Innovations:
- Multi-level navigation architecture leveraging HNSW graphs
- Primary-based cluster representation for efficient memory utilization
- Innovative sample-based clustering strategy with minimal computational expense
MAVANN
Metadata-Aware Vector Approximate Nearest Neighbor
MAVANN introduces a novel approach to metadata filtering in vector databases, integrating metadata directly into the vector search process for dramatically improved performance without sacrificing result quality.
Key Innovations:
- Metadata-aware vector navigation for efficient pre-filtering during search
- Dynamic re-routing based on both vector similarity and metadata constraints
- Up to 20x faster query performance with complex metadata filtering
Unlock Your Data's Potential
Leverage embeddings, hybrid search, and knowledge graphs to power applications in search, recommendations, anomaly detection, and more.
Retrieval Augmented Generation (RAG)
Enhance the quality of AI-generated content. Leverage Cosdata's powerful hybrid search capabilities, combining dense and sparse vectors with knowledge graphs, to retrieve contextually relevant data points for retrieval-augmented generation.
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Advanced Search
Elevate your applications with Cosdata's advanced search technology. Seamlessly process high-dimensional data for nuanced similarity searches, and gain deeper insights with our integration of dense vectors and structured knowledge graphs.
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Recommendation Systems
Build responsive, data-driven recommendation systems with Cosdata's hybrid search. Utilize multiple vectors and relationships in a single query to generate highly personalized, relevant recommendations at scale.
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