Lunr.js is described as 'Lunr Search is a compact, full-featured search tool that doesn't require external server-side services. It offers language processors for accurate user query results and can be adjusted to suit your content. Lunr works in your browser or on a server with node' and is an app in the development category. There are more than 10 alternatives to Lunr.js for a variety of platforms, including Linux, Web-based, Mac, Windows and SaaS apps. The best Lunr.js alternative is Elasticsearch, which is both free and Open Source. Other great apps like Lunr.js are Apache Solr, Sphinx (search engine), Elasticlunr and ItemsAPI.
Unmatched relevance. Real-time insights. Anything is possible — when the precision of search meets the intelligence of AI.
Solr is an open source enterprise search server based on Lucene search library, with XML/HTTP and JSON APIs. Its major features include powerful full-text search, hit highlighting, faceted search, dynamic clustering, database integration, and rich document handling.
Sphinx is a software search engine designed with indexing database content in mind. It currently supports MySQL, PostgreSQL, and ODBC-compliant databases as data sources natively. Other data sources can be indexed via pipe in a custom XML format.
Elasticlunr.js, lightweight full-text search engine in Javascript for browser search and offline search. Elasticlunr.js is developed based on Lunr.js, but more flexible than lunr.js. Elasticlunr.js provides Query-Time boosting and field search.
The goal of ItemsAPI is creating search application without spending time for backend. You just provide json data and your backend is ready to go.
Qdrant (read: quadrant) is a vector similarity search engine and vector database. It provides a production-ready service with a convenient API to store, search, and manage points—vectors with an additional payload Qdrant is tailored to extended filtering support.
Enterprise search, simplified. Cloud-based enterprise search solution that search across all of your organization’s content sources — Aconex, Procore, Dropbox, Microsoft Sharepoint, Onedrive, and more.
Generally speaking, fuzzy searching (more formally known as approximate string matching) is the technique of finding strings that are approximately equal to a given pattern (rather than exactly).
Milvus is an open-source vector database built to power embedding similarity search and AI applications. Milvus makes unstructured data search more accessible, and provides a consistent user experience regardless of the deployment environment.
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