Explore ParadeDB's v2 API that eliminates schema duplication, simplifies tokenization, and provides transparent search operators for intuitive SQL-based full-text search.
ParadeDB — Search without a second system
One Postgres for your application data, full-text search, vector retrieval, and aggregations. Home of the pg_search extension.
Getting started with SQLite Full-text Search By Examples
This tutorial shows you how to use SQLite full-text search feature by using the FTS5 virtual table module.
🔎 sqlx base - Google Search
🚀 Announcing readwise-vector-db: Supercharge Your Readwise Library with Local, Semantic Search
Parallel Web Systems | Infrastructure for intelligence on the web
Parallel's new FindAll API turns natural language queries into custom datasets from the web. It finds entities like companies, people, or locations based on your criteria, then enriches them with structured data—all with citations. FindAll Pro achieves 61% recall, 3x better than competitors.
WikiKV: Schema-Evolving Path-Indexed Storage for Hierarchical Knowledge Navigation
LLM-curated hierarchical knowledge bases, namely a tree-structured wiki whose nodes summarize an underlying corpus, have become a dominant substrate for retrieval-augmented applications, yet their storage layer is still treated as an implementation detail. This workload is hierarchical, query-intensive, and continuously evolving, and no existing storage model natively captures all three properties at once. We present WikiKV, a path-indexed key-value storage model purpose-built for this workload, comprising three components: (i) a data-driven schema that bootstraps the hierarchy via Intent-Anchored Schema Induction and refines it through Continuous Evolution Operators; (ii) a consistency protocol for the path-indexed storage model that precludes partial-read observations under concurrent offline rewrites without read-path locking; and (iii) a budgeted navigation operator whose search-accelerated routing reduces the expected number of LLM-assisted descent steps from d to O(1) while preserving anytime semantics with progressively refined answers. We evaluate WikiKV through real-world deployment for the WeChat Official Account AI Assistant and benchmark it against diverse baselines on the AuthTrace dataset, where it achieves balanced low per-operator latency across four query operators against relational, graph, and FS backends, and reaches 63.2% end-to-end answer correctness, exceeding multiple RAG baselines, with the gap widening on low- and high-fan-in multi-document questions. Ablation study further confirms the effectiveness of WikiKV's components.
Semantic Data Modeling, Graph Query, and SQL, Together at Last?
Our teams advance the state of the art through research, systems engineering, and collaboration across Google.
Meilisearch: Unified Search & AI Retrieval Platform
Build lightning-fast search and AI retrieval with Meilisearch. Open-source, developer-friendly search engine trusted by 20,000+ teams worldwide.
Graceful database schema evolution: the PRISM workbench: Proceedings of the VLDB Endowment: Vol 1, No 1
Supporting graceful schema evolution represents an unsolved problem for traditional information systems that is further exacerbated in web information systems, such as Wikipedia and public scientific databases: in these projects based on multiparty ...
Introduction
A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.
Dremel: interactive analysis of web-scale datasets: Proceedings of the VLDB Endowment: Vol 3, No 1-2
Dremel is a scalable, interactive ad-hoc query system for analysis of read-only nested data. By combining multi-level execution trees and columnar data layout, it is capable of running aggregation queries over trillion-row tables in seconds. The system ...
Spacedrive — A local-first data engine for everything you own
Index any data source. Search everything from one place. Keep it on your machine.
Here's how we leverage @semble.so's wonderful service in search results 👀. This is currently the only working search integration but 20+ more are in the works right now!
