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Qdrant - A Vector Search Engine in Rust

Rust via YouTube

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Overview

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This talk examines how a vector search engine works and why Rust suits its implementation. It covers similarity models, HNSW indexing, payload filters, concurrency, and distributed consensus through Qdrant’s architecture.

Syllabus

Intro
Qdrant
Evolution of Search
Neural Search
Similarity Models
Vector Search Engine
Example
Additional Data
Implementation
Index
A N Search
Hnsw
payload filters
distance metrics
similarity function
naive product
CMD
Static vs Dynamic
CMD code
DOT benchmark
Architecture
Concurrent Programming
Mutex RWLock
Deadlocks
Deadlock Detection
Distribute
Raft Consensus
Conclusion

Taught by

Rust

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