5 dépôts
Background construction of database indexes to avoid blocking query performance.
Distinct from Database Indexes: Specifically addresses the asynchronous nature of index building, not just the data structure.
Explore 5 awesome GitHub repositories matching data & databases · Asynchronous Indexing. Refine with filters or upvote what's useful.
LanceDB is a vector database and columnar data store designed to function as a versioned dataset manager and vector search engine. It serves as a high-performance backend for indexing and retrieving high-dimensional embeddings, providing the foundation for machine learning data pipelines. The system distinguishes itself through a combination of cloud-native object storage and immutable version tracking, allowing for data time-travel and reproducible AI experiments. It integrates hybrid search capabilities, merging dense vector similarity with BM25 full-text search and SQL-like scalar filters
Builds vector or scalar indexes on table fields asynchronously to accelerate search operations.
ParadeDB is a database extension that integrates full-text search, vector database capabilities, and real-time analytics directly into a relational engine. It functions as a plugin that adds new storage and query execution capabilities to an existing database architecture. The project distinguishes itself by supporting hybrid search workflows that combine lexical keyword matching with dense and sparse vector similarity in a single query. It utilizes reciprocal rank fusion to merge these ranked result sets and employs logical replication to synchronize data from external instances, removing th
Increases ingestion speed by buffering writes and merging index segments asynchronously in the background.
Ships microtask-scheduled batch indexing that keeps the UI responsive during bulk document inserts.
RavenDB is a multi-model NoSQL document database designed for high-performance, ACID-compliant data storage. It persists structured information as schema-flexible JSON documents and utilizes a unit-of-work session pattern to track entity changes and batch modifications into atomic transactions. The platform is built on a distributed architecture that supports horizontal scaling through sharding and ensures high availability via multi-node, master-to-master cluster replication. The database distinguishes itself through a self-optimizing query engine that automatically creates and maintains ind
Processes raw documents into searchable indexes in the background to maintain high performance during write operations.
Vald is a distributed, cloud-native search engine designed for high-dimensional vector data. It functions as an approximate nearest neighbor search platform, enabling the identification of similar data points across massive datasets through horizontal scaling and distributed indexing. The system is built for container orchestration environments, utilizing custom resource controllers to automate cluster lifecycle management and infrastructure state. It employs graph-based indexing to perform rapid similarity lookups and supports zero-downtime operations by decoupling index construction from qu
Performs index construction in the background to ensure continuous availability during data modifications.