Qdrant 1.15 - Smarter Quantization & better Text Filtering

Qdrant 1.15 introduces several enhancements aimed at improving vector search and text filtering capabilities. The update includes advanced quantization techniques, such as asymmetric quantization and 1.5 and 2-bit quantization, which optimize memory usage and accuracy for high-dimensional vectors. The release also features significant upgrades to the text index, including a new multilingual tokenizer supporting languages like Japanese and Chinese, stopwords filtering, stemming for better query matching, and phrase matching for exact searches. Additionally, Maximal Marginal Relevance (MMR) reranking is introduced to balance result relevance and diversity, improving search output in dense datasets. The transition from RocksDB to Gridstore as the default storage backend enhances ingestion speeds and storage management, while optimizations such as HNSW healing and connectivity estimation improve indexing efficiency. The release also includes an updated Web UI for easier collection configuration and encourages best practices through an intuitive setup flow.