Yandex B2B Tech Integrates Hybrid Full-Text and Vector Search in Single YDB Query

Yandex B2B Tech has added hybrid search to its YDB database, allowing full-text and vector approaches to run together inside one SQL query. The update helps small and medium businesses as well as large corporations locate exact document identifiers while also matching semantic meaning in descriptions, even when wording differs. Full-text search handles precise elements such as policy numbers, codes, and names, whereas vector search identifies conceptual similarity. Results from both methods are merged and ranked within the same transaction, keeping all data inside a single database instance. This removes the need to maintain a separate search engine and vector store or to reconcile information between them. The technology is aimed at chatbots, recommendation systems, and AI assistants that process technical content where both exact codes and human-readable problem descriptions matter equally. Hybrid search is now available in the on-premises YDB 26.3 release and in the cloud-based Managed Service for YDB.

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Yandex B2B Tech has introduced hybrid search capabilities to its YDB database platform, combining full-text and vector search methods within a single query.

The new feature enables organizations to solve two tasks simultaneously: locating an exact document identifier such as a policy number and interpreting the semantic meaning of surrounding text, even when alternative phrasing is used. Full-text search manages precise matches for words, names, and codes, while vector search identifies conceptual similarity across documents.

According to the YDB development team, the two approaches complement each other effectively. In insurance-related queries, for example, the system can return an exact policy number alongside descriptions of incidents that match in meaning despite different wording. Results are combined and ranked inside one SQL query, simplifying application logic.

A key practical advantage is that all data remains in a single database. Companies no longer need to operate a separate search engine and vector database or monitor consistency between the two systems. Indexes are updated together with the underlying data as part of the same transaction, reducing synchronization overhead and potential data drift.

The technology is designed for chatbots, recommendation services, and AI assistants that require more than simple keyword matching. It is especially relevant when processing technical information where both precise part codes and natural-language problem descriptions must be handled accurately.

Hybrid search is available in the corporate edition of YDB 26.3 for on-premises deployment as well as in the cloud Managed Service for YDB.

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