ZeroDB: High-Performance Vector Database for AI Applications

# ZeroDB: High-Performance Vector Database ZeroDB is AINative's purpose-built vector database designed for AI applications requiring semantic search, similarity matching, and real-time vector operations. ## Why Vector Databases? Traditional databases store data in rows and columns. Vector databases store embeddings - numerical representations of data that capture semantic meaning. ### Use Cases - **Semantic Search**: Find similar documents, images, or data - **Recommendation Systems**: Suggest related content - **RAG Applications**: Retrieval-Augmented Generation - **Anomaly Detection**: Identify outliers in data ## Getting Started with ZeroDB ```python from zerodb import ZeroDBClient # Initialize client client = ZeroDBClient( project_id="your-project-id", api_key="your-api-key" ) # Store vectors client.upsert( namespace="documents", vectors=[ { "id": "doc-1", "values": embedding, # 1536-dimension vector "metadata": {"title": "Hello World", "category": "blog"} } ] ) # Search results = client.query( namespace="documents", vector=query_embedding, top_k=10, filter={"category": "blog"} ) ``` ## Advanced Features - **Quantum Compression**: Reduce storage by 50% while preserving accuracy - **Hybrid Search**: Combine vector and traditional search - **Real-time Indexing**: Instant updates to search results - **Multi-tenant**: Isolated namespaces for different use cases ## Performance - **Query Latency**: <10ms for 1M vectors - **Throughput**: 10K+ queries per second - **Scalability**: Billions of vectors supported Start building intelligent search today with ZeroDB!

ZeroDB: High-Performance Vector Database for AI Applications

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