Every search interface relies on a fast back-end data-indexing process that keeps its search results up to date in as timely a manner as possible. But search indexing is only one side of the coin. The other side is the real-time speed of a high-quality relevant search engine. By Peter Villani.
The article then explains how you could imrpove search performance for Algolia NoSQL database:
- Indexing for search
- Indexing to create a company-wide, multi-purpose, searchable data layer
- Indexing as a “matchmaker” – the collaborative indexing use case
- Best practices for fast indexing performance (with code snippets)
- Batch indexing instead of updating one record at a time
- Batch indexing instead of updating one record at a time
- Partial indexing (updating only changed attributes)
For all search engines, the search request is the highest priority, with indexing a (very) close second. There are several reasons for this, but the most important is a business argument: every search is a potential game changer, a path to a conversion. Any slow or dropped search request, or irrelevant result, is a potential financial or business loss. Nice one!
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