Although in-site search has long been available from general web search providers such as Google, this is typically done as a subset of general web searching. The search engine crawls or spiders the web at large, including the client site, and then offers search features restricted to only that target site. This is a large and complex task, available only to large organisations at the scale of Google or Microsoft.
Algolia's product only indexes their clients' sites and so the search task is far simpler. Data for the client site is pushed from the client to Algolia via a RESTful JSON API, then the search box is added simply to the client's web pages. This search model is intended to give the performance and sophistication advantages of a full in-house search engine operating on the native web site back-end database, but with the simplicity of setup of using a site-restricted Google search.
Algolia claim a number of advantages for their approach, including speed of response from searching a single site rather than the entire web Moreover, as Algolia's search can be tailored to the client site, its known structure and its metadata facets, the search offered can be smarter and more site-specific than a generalised web text search. This improves the relevance of search results as searching may take the semantics of site content into account. A web site selling both puppies and dog clutches could avoid the search confusions and homonymy that bedevil the simple text-based search approaches.
Algolia documented an attempt to remove any single point of failure in the architecture and proposed a worldwide infrastructure called Distributed Search Network to efficiently reply to a search query from any location.
The DSN feature allows to set the locations in Algolia's network where the data should be duplicated. The API and queries are routed from the end-user’s browser or mobile application to the closest location in the network. This set up reduces latency for end users and improves availability for searches.