Скачать или смотреть Search Engines with Vector Support | Elasticsearch, OpenSearch & Solr

Traditional search engines were built for text-based keyword search—but now they’re evolving with vector search capabilities. 🔍⚡

In this video, we explore search engines with vector support, where platforms like Elasticsearch, OpenSearch, and Solr extend beyond simple text matching to handle embeddings and approximate nearest neighbor (ANN) search.

You’ll learn:
✅ What vector support in search engines means
✅ How keyword + semantic hybrid search works
✅ Key examples: Elasticsearch, OpenSearch, and Solr
✅ Benefits: scalability, strong text search foundation, and hybrid queries
✅ Limitations compared to purpose-built vector databases
✅ Where to apply them: enterprise search, knowledge retrieval, AI-driven applications

If you’re already using search engines for information retrieval or enterprise systems, this video shows how vector extensions enable a bridge between classic keyword search and modern AI semantic search. 🚀

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