Every category where a model named Elasticsearch for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.

Category	Function	Share	Rank	Negative rate	Labels	Quadrant	Since September 2026
Ecommerce search and merchandising	Marketing	0%	27 of 74	36%	14	criticized challenger

Movement

This is the first edition on this tier, so no move can be computed for Elasticsearch yet. From the next edition this section shows, per buyer segment and per category, whether its share moved by more than the measured noise floor.

By model

How each model treated Elasticsearch across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.

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Model	Alternative	Mention	Negative	Labels
Claude Haiku 4.5	0	0	1	1
GPT-5.4 mini	1	0	0	1
Gemini 3.5 Flash	0	0	2	2
Perplexity Sonar	2	0	0	2
Grok 4.20	0	0	0	0
Mistral Small	0	0	0	0
DeepSeek V4 Flash	0	0	0	0
Llama 4 Maverick	0	0	0	0
Qwen 3.7 Flash	0	1	1	2
Kimi K2	1	1	1	3
GLM 4.7 FlashX	0	1	0	1
MiniMax M2.5	1	0	0	1
GPT-6 Luna	0	0	0	0
Muse Glimmer 30B	0	1	0	1

By framing

Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.

FramingLabels by classFirst choices

Direct1 labelNone

Paraphrase9 labels1

Comparative6 labelsNone

Budget-constrained5 labels1

Scale-constrained3 labelsNone

Negative12 labelsNone

First choiceAlternativeMentionNegative36 labels in all, every segment counted; 2 of the 2 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.

What the models said for it

Verbatim evidence the judge attached to positive labels.

“Open-source search like Meilisearch, Typesense, or Elasticsearch can be cheaper on software cost” Perplexity Sonar · Ecommerce search · budget prompt · alternative

“Elasticsearch if you have a strong engineering team and want maximum control/customization” GPT-5.4 mini · Ecommerce search · paraphrase prompt · alternative

“self-hosted Meilisearch, Typesense, or Elasticsearch if you have engineering capacity” Perplexity Sonar · Ecommerce search · negative prompt · alternative

“Best for: Technical teams wanting full control and customization” Kimi K2 · Ecommerce search · comparative prompt · alternative

And against it

Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.

“Raw, Self-Hosted Open-Source Infrastructure (Avoid for Merchandising)” Gemini 3.5 Flash · Ecommerce search · negative prompt · hard negative

“heavyweight custom-built solutions (like raw Elasticsearch) or ultra-enterprise suites (like Coveo or Bloomreach) are often too expensive and complex to maintain” Gemini 3.5 Flash · Ecommerce search · paraphrase prompt · soft negative

“Elasticsearch has significant technical complexity requiring specialized engineering for setup, tuning, scaling, and maintenance.” Claude Haiku 4.5 · Ecommerce search · negative prompt · soft negative

“Licensing concerns — Recent licensing changes have raised costs and uncertainty” Qwen 3.7 Flash · Ecommerce search · negative prompt · soft negative

Named alongside

The products named in the same answers as Elasticsearch, over the 36 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Elasticsearch was named but was not.

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ProductSame answerTook the first choice insteadHead to head

Algolia34 of 369Not among the top eight

Coveo21 of 364Not among the top eight

Bloomreach Discovery21 of 362Not among the top eight

Klevu19 of 363Not among the top eight

Searchspring15 of 360Not among the top eight

Constructor11 of 362Not among the top eight

Doofinder9 of 365Not among the top eight

Nosto7 of 361Not among the top eight

Typesense7 of 361Not among the top eight

Meilisearch7 of 360Not among the top eight

A head-to-head page exists where both products are among a category's top eight. The other rows are the same fact without a page behind them, so they link to the product instead.

What carried it into the answer

The sites and pages cited by the answers that named Elasticsearch. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 33 of the 36 answers that named Elasticsearch and are not a share of its labels.

Domains cited

netguru.com19

g2.com17

guideflow.com17

clerk.io13

zoovu.com13

algolia.com11

gitnux.org11

cs-cart.com10

ringly.io10

valiantceo.com10

No domain is on file for Elasticsearch, so its own site is not marked.

Pages cited

netguru.com/blog/ecommerce-search-solutions-product-discovery16

guideflow.com/blog/best-ecommerce-search-software14

zoovu.com/blog/best-ecommerce-search-engine13

clerk.io/blog/choosing-search-engine-in-202610

cs-cart.com/blog/best-ecommerce-search-engines10

valiantceo.com/the-7-best-ecommerce-search-and-discovery-platforms10

gitnux.org/best/ecommerce-merchandising-software9

voyado.com/resources/blog/top-ecommerce-search-solutions9

Pages are listed as the models cited them.

Search and answers

Where Elasticsearch stands in Google search beside where it stands in the models' answers.

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In search

Google, US estimates

Searches for its name, Google: 12,100 a month (“elasticsearch”)
AI search demand for its name, est.: 2,798 a month
Its own site: No site of its own on file, so no site figures

In answers

This edition

Share of first choices

rank 27 of 74 in ecommerce search

Segment leader

25%

Algolia

First choices: 2 across its categories
Named in: 36 answers
Its own site cited: No site on file to match

Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.

Names read as Elasticsearch

What the judge wrote, as written, with how often. The vendor table decides that these count as Elasticsearch; a claim can dispute any of them.

Elasticsearch (Open Source / Elastic Cloud) 1Elasticsearch / Elastic Site Search 1Solr/Elasticsearch 1

Follow Elasticsearch

An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.

Already following? Everything you follow, with a stop for each.

Is this your product?

Claim this page

Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Elasticsearch's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Elasticsearch, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

What a new claim receivesHide what a new claim receives

A new claim receives the current edition's vendor brief for Elasticsearch by email, built from the raw record of the edition. It shows:

where Elasticsearch is named, by buyer and by framing, and which cells hold its first choices;
the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
its vocabulary against the segment leader's, and the pages the models cited;
who was chosen in the answers that did not name Elasticsearch, and every reason the record gives;
a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
one page of published figures cleared to show a buyer.