/plushcap/analysis/aerospike/aerospike-aerospike-search-adds-vector

Smart search, smarter results: Inside an Aerospike-powered search engine

What's this blog post about?

Aerospike-powered search engine, also known as Aerospike Vector Search, enhances website search by combining keyword precision and semantic understanding to deliver high-quality results. The search engine uses a hybrid model that marries contextual understanding of vectors with the precision of keyword search, allowing it to grasp the meaning of user queries. This approach enables the search engine to handle typos, synonyms, and other fuzzy lookup issues more effectively than traditional keyword-based searches. Aerospike Vector Search achieves this by using machine learning models to create vector embeddings that capture the semantic meaning of text data, which are then used for fast and efficient searching across large datasets. The search engine's performance is improved through the use of a unified database, an effortless API, and a seamless process for adding vectors and querying the database.

Company
Aerospike

Date published
Dec. 11, 2024

Author(s)
Art Anderson

Word count
871

Language
English

Hacker News points
None found.


By Matt Makai. 2021-2024.