The Scalable SQL, Full-Text and Vector Platform for Gen AI

SingleStore has re-implemented its full-text search engine based on the widely used Apache Lucene (JLucene) platform, providing fuzzy search, proximity search, boosting, BM25 scoring, and support for JSON data type. The new implementation runs JLucene in a co-process next to the SingleStore service process on each node, minimizing data copying for excellent performance. Full-text search is now available over JSON fields directly, with examples provided for fuzzy search, proximity search, and boosting. Vector search enhancements include filtered ANN support and a new vector range search feature. The system supports boosting of terms, BM25 scoring, and proximity search, allowing developers to rank documents with favored terms higher. SingleStore's JSON data type has become popular since its introduction, and the new release further enhances its capabilities. The system is designed to help developers build modern, intelligent apps that combine transaction processing, analytics, search, and gen AI without the need for multiple data stores or complexity.

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