Algolia vs Google Retail Discovery AI

Compare the tactical differences between Algolia and Google Retail Discovery AI to see which approach is best for meeting your needs.

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AlgoliaGoogle Retail Discovery AI

Overview

Google has a history of site-search products that it launched and later abandoned — Google Custom Search Engine (GSCE), Google Search Appliance (GSA), Google Site Search (GSS), and Google Programmable Search Engine to name a few. Now they have released several new retail-specific search solutions, including Google for Retail and Retail Discovery AI for on-site product search. At Algolia, we've been 100% focused on-site search since day 1 for the past 10+ years.

API-first end to end A Search & Discovery for product and full-size search

Usage pricing with pay-as-you-go and enterprise

17,000+ customers supporting over 1.5 trillion searches a year - rare 99.999% availability SLA with customers WW

Offers multiple products to support retailers for internet and on-site product search

Add on to Google Cloud - ability is support scale, performance, and relevance for site search consistently for the enterprise customers is unknown at this time

Google retail search has less than 100 customers; nobody has used it for more than 1 year

Search & use of AI

Although Google was an early pioneer in AI, newer businesses have pushed above and beyond Google’s AI capabilities. At Algolia, we have developed end-to-end search specifically to meet the needs of businesses for site and API-based search applications at any scale.

AI-native AI Search with end-to-end AI processing with both keywords and vectors ensuring the most relevant results at scale

AI Search

AI-powered query categorization, recommendations, and personalization boosted by industry’s only AI powered automatic query categorization

While Google has vector solutions, nobody EXCEPT Algolia has been able to do this at scale while keeping the costs at keyword level for realistic enterprise-wide applications as well as  complexity levels to a minimum for broader adoption

Not designed for a holistic ecommerce buyer journey/experience as they do not serve federated search content

Complex setup (VPC) with high cost to work with data outside of Google cloud (not federated)

Uses Approximate Nearest Neighbor (ANN) with asymmetric hashes for encryption. Searching through vectors using ANN is much more expensive (through the tree structure vs. relational db model). Memory intensive high latency query processing is especially troublesome for high volume or frequent updates

Architecture

Algolia offers a composable end to end AI Search & Discovery platform built with an API-first approach so it can be connected with any environment easily and managed without additional cost and complexity. Coveo, on the other hand, pushes to be a service provider for implementation that may take upwards of a full year.

API-first to work in any environment, different-use cases — much more configurable

Built for speed and scale with results optimized for each customer - sub 20ms on any query, even with catalogs of 90 Million + SKUs

Allows for multiple indexes which can be searched (federated) at once

Designed for both business and technical users

Pre-built, packaged connectors to Salesforce, ServiceNow, Zendesk, Adobe, and other for indexing and federated search - while they connect with other platforms but they’re not indexed all the same, resulting in poor search results

Good enterprise search capabilities for pre-packaged connectors

REST API for indexing and querying an index; limited availability for different language APIs

Deployment

Google Retail search is a merge of APIs using Google Cloud, their retail API and data sitting within Google Retail to form a solution aimed at improving product discovery. Algolia can be deployed in minutes via simple configuration options or an API.

Self-service, faster time to value with dozens of pre-built, configurable front-end widgets for fast deployment

Extensive dev support to build: <12 weeks to go live

Easy to use UX/UI widgets and front-end library to custom-make any end-user experience in minutes

Transparent, simple pricing

Slower time to value; UX/UI needs heavy dev load; minimal front-end libraries

GRS can take up to 12 weeks for just backward readiness, more months to go live

Cloud platform pricing based on queries, API calls, prediction requests, and more

Usability

After being deployed, Algolia is built for anyone — technical or non-technical users — to run, configure, and manage results. Google Retail Discovery AI is built only for engineers.

API-first to work in any environment, different-use cases

Built for speed and hyper-scalability with results optimized for each customer

Allows for multiple indexes which can be searched (federated) at once

Designed for both business and technical users with no code drag and drop environments

API-first with various language libraries

Very scalable on Google Cloud; but not efficient outside of Google environment (in contrast, Algolia operates equally efficiently in all public cloud environments)

Designed for technical users only; no business dashboards or no-code merchandising - needs heavy dev workload from dev with minimal front-end library support provided

Merchandising

Algolia Merchandising Studio is a free application that gives merchandisers the power to easily manage and curate campaigns. Google doesn’t offer anything similar.

Free Merchandising Studio designed for merchandisers to build custom campaigns and ease of use

Full-control over search results and catalog listings

Ability to create rules or manually pin results — no-code required

No direct merchandising capabilities

Google Merchant Center for displaying results on Google’s internet search

Boosting and filtering capabilities to promote products built for engineers

Search that understands

More than 17,000 customers in 150+ countries selected Algolia to grow customer satisfaction and sales. Because when your customers feel understood, they click and they come back.

See customer stories
The Times
Algolia is a breeze to work with. With Algolia, our editorial team has seen significant productivity improvements when building the daily online edition of The Times and weekly edition of The Sunday Times, with search being 300-500 times faster than our prior solution.

Matt Taylor

Editorial Product Manager @ The Times
LTK
Algolia is very fast — able to keep up with our level of traffic… The API and SDK options are really great, and the ability to handle traffic at scale (we have a high volume)

Matt Goorley

Engineering Manager @ LTK
Swedol
[Algolia] was very professional from the start. We had a great Customer Success Manager and team that provided a lot of help and was a great partner.

Clint Fischerström

Head of Ecommerce @ Swedol
Hershey
I think we’ve grown leaps and bounds with Algolia. There's a lot of features that we still can tap into, which is great because I feel like we've gotten a ton out of it already.

Geoff Lyman

Digital Experience Solutions Manager @ Hershey's
Shoe Carnival
Instead of having to go into the back end and the catalog—which would have been a technical headache—we were able to figure it out in a matter of a day, test it, and ‘boom’ it’s live.

Courtney Grisham

Director of E-Commerce @ Shoe Carnival

An award-winning solution