Intelligent Partitioning Techniques for Vector Databases
Deep Searcher innovatively introduces the concept of database partitioning into the vector search domain. By establishing logical partitions in vector databases such as Milvus, the system can realize 'precise search domain' control: HR query only scans employee file partitions, and R&D search only accesses technical document partitions. This design solves the bottleneck of search efficiency caused by the proliferation of enterprise data volume.
In terms of technical implementation, the project provides a complete set of partition management APIs: supporting the establishment of partition indexes by department, time, project and other dimensions; allowing the setting of cross-partition federated searches; and providing partition-level privilege control. Measurement data shows that in the enterprise environment of ten million documents, the partitioning policy can reduce the search response time from seconds to milliseconds.
An application example from a multinational organization shows that by partitioning the global business by geography, regional managers can access local sales data 8 times faster, while eliminating distracting information from unrelated regions. This intelligent partitioning capability is Deep Searcher's core competency that differentiates it from ordinary search tools.
This answer comes from the articleDeep Finder: open source project for deep inference search using local knowledgeThe
