#scylladb (21)
- USearch & ScyllaDB Vector Search Practical Field Guide
Embark on a comprehensive journey to master the USearch library for high-performance vector search, particularly with ScyllaDB, from fundamentals to advanced deployment.
- What are Vector Embeddings? The Language of AI
Unlock the mystery of vector embeddings! Learn what they are, why they're vital for modern AI, and how they transform data into a language machines understand for tasks like similarity search.
- USearch: Core Concepts, Installation, and Vector Search
Learn USearch core concepts, install the library, and perform your first vector search using practical Python examples for a strong foundation.
- Your First Vector Search with USearch
Take your first steps with USearch! Learn to initialize a vector index, add data, and perform similarity searches, understanding the core concepts of high-dimensional data retrieval.
- ScyllaDB: A Real-time Database for AI (Overview)
Explore ScyllaDB's architecture, its role in real-time AI applications, and how it provides massive-scale vector search capabilities, powered by USearch.
- Storing Vectors in ScyllaDB: The Vector Data Type
Dive into ScyllaDB's native vector data type, learn how to define vector columns, understand distance metrics, and store vector embeddings for efficient similarity search.
- Perform Vector Similarity Search Directly in ScyllaDB
Readers will learn to integrate vector search into ScyllaDB, create vector columns, build indexes, and perform similarity searches using CQL.
- Understanding USearch Indexing Strategies
Dive deep into USearch indexing strategies, focusing on HNSW, understanding their impact on performance and recall, and applying them for efficient vector search with ScyllaDB.
- Vector Distance Metrics and Their Impact
Explore vector distance metrics like Euclidean, Cosine, and Dot Product, understanding their role in USearch and ScyllaDB for accurate similarity search.
- Optimizing USearch Performance: Memory & Latency
Dive deep into optimizing USearch performance within ScyllaDB, focusing on memory management, latency reduction, and fine-tuning vector index parameters for real-time AI applications.
- Scaling ScyllaDB Vector Search for Billions of Vectors
Unlock the power of ScyllaDB and USearch to build highly scalable vector search solutions capable of handling billions of vectors with low latency and high throughput.
- Advanced USearch Features: Quantization & Compression
Dive into advanced USearch features: quantization and compression. Optimize vector search for memory, speed, and scale, balancing accuracy with performance in your AI applications.
- Designing Real-world Vector Search Systems with ScyllaDB and USearch
Learn to design and understand production-ready architectures combining USearch and ScyllaDB for scalable, high-performance vector search applications.
- Building a Movie Recommendation System
Learn to build a real-time movie recommendation system using USearch for efficient vector similarity search and ScyllaDB for scalable, low-latency vector storage.
- Implementing Semantic Search for Documents
Dive into practical semantic search by building a document search engine. Learn to generate embeddings, store them in ScyllaDB, and query with USearch for intelligent results.
- Fraud Detection with Vector Similarity
Learn to apply USearch and ScyllaDB for real-time fraud detection using vector similarity, building on prior knowledge of embeddings and scalable databases.
- Monitoring and Debugging Vector Search Systems
Master monitoring and debugging USearch-powered vector search with ScyllaDB. Learn to identify performance bottlenecks, troubleshoot issues, and ensure system reliability using Prometheus and Grafana.
- Deployment Strategies for High-Availability
Explore robust deployment strategies for USearch-powered vector search with ScyllaDB, focusing on achieving high-availability, fault tolerance, and scalability for critical AI applications.
- Data Lifecycle Management for Embeddings
Master the critical aspects of managing the full lifecycle of vector embeddings, from creation to updates and deletion, using USearch and ScyllaDB for optimal performance and data freshness.
- The Future of Vector Search with USearch and ScyllaDB
Learn about emerging vector database trends like hybrid search and multimodal AI, and how USearch and ScyllaDB will shape real-time AI applications.
- USearch and ScyllaDB for Vector Search Guide
Learn to implement efficient vector search applications using the USearch library and its integration with ScyllaDB, covering fundamentals and advanced techniques.