What Is Vector Search? Difference Between Vector & Semantic Search Explained [Quick Question Ep. 5]

What is vector search? In this breakdown, learn how vector search leverages machine learning to capture the meaning and context of unstructured data by transforming it into a numeric representation that is stored in a vector database. This video also explains the difference between sparse and dense embeddings, and how vector search differs from semantic search and lexical search.

0:00 - What is Vector Search?

0:29 - How Vector Search Works (inference → embeddings → vectors)

0:45 - Vector Search vs Semantic Search

0:58 - What are Vector Embeddings?

1:11 - Sparse Embeddings & Text Expansion

1:33 - Dense Embeddings

1:56 - Wrap‑Up + Where to Learn More

Additional Resources:
Learn more about semantic search: https://www.elastic.co/what-is/semantic-search
Learn more about Elasticsearch: https://www.elastic.co/elasticsearch

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About Elastic
Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale. Elastic’s solutions for search, observability, and security are built on the Elastic Search AI Platform — the development platform used by thousands of companies, including more than 50% of the Fortune 500.

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