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Index › Products › Great Expectations · October 2026 Edition
2 categories · Ranked

Great Expectations

92Judge labels
2First choices
15Negative labels
14 / 14Models named it
2Categories
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.8, every buyer segment counted.
Best standing
2% in Data observability for mid-market buyers
Rank 10 of 110 in the mid-market standingaccepted challenger
0 of 14 models made it the first choice on the direct prompt; 16% of its 37 labels there were negative.
What the models named instead of Great Expectations →
By buyer segmentRead the same way at every buyer size.
In data observability · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading

Standing by category

Every category where a model named Great Expectations 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.
CategoryFunctionShareRankNegative rateLabelsQuadrantSince September 2026
Data quality and observabilityData platform2%10 of 11016%37accepted challenger
Data catalogs and governanceData platform0%30 of 830%1under 10 labels · led by Atlan at 44%

Movement

This is the first edition on this tier, so no move can be computed for Great Expectations 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 Great Expectations across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
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ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.501113
GPT-5.4 mini12003
Gemini 3.5 Flash03014
Perplexity Sonar00101
Grok 4.2001203
Mistral Small00202
DeepSeek V4 Flash02125
Llama 4 Maverick00101
Qwen 3.7 Flash05016
Kimi K202002
GLM 4.7 FlashX10012
MiniMax M2.502103
GPT-6 Luna00101
Muse Glimmer 30B10102

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
Direct8 labelsNone
Paraphrase11 labelsNone
Comparative32 labels6not counted in share
Budget-constrained14 labels2
Scale-constrained10 labelsNone
Negative17 labels1not counted in share
First choiceAlternativeMentionNegative92 labels in all, every segment counted; 2 of the 9 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.

“### 1. Great Expectations — Open‑Source Framework ... Pros: Free, highly customizable, widely adopted” GLM 4.7 FlashX · Data observability · comparative prompt · first choice
“Great Expectations and Soda Core lead for data engineering teams that embed validation in CI/CD pipelines.” Muse Glimmer 30B · Data observability · comparative prompt · first choice
“best value choice is usually Great Expectations (GX Core) or Soda Free/open-source first” GPT-5.4 mini · Data observability · budget prompt · first choice
“If you have strong internal engineering, Great Expectations + Soda can work but require more hands-on management” MiniMax M2.5 · Data observability · scale 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.

“Data Quality Platforms to Avoid or Be Cautious About ... Great Expectations (OSS Version) ... Best avoided if: You need real-time monitoring, have large datasets” GLM 4.7 FlashX · Data observability · negative prompt · hard negative
“Great Expectations is widely criticized in the data engineering community for being overly complex, heavy, and difficult to configure.” Gemini 3.5 Flash · Data observability · negative prompt · soft negative
“it avoids both the enterprise pricing overhead of Monte Carlo and the DIY complexity of open-source options like Great Expectations” DeepSeek V4 Flash · Data observability · direct prompt · soft negative
“Steep learning curve is the #1 complaint... Not a true observability platform.” DeepSeek V4 Flash · Data observability · negative prompt · soft negative

Named alongside

The products named in the same answers as Great Expectations, over the 92 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Great Expectations was named but was not.
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ProductSame answerTook the first choice insteadHead to head
Soda59 of 9214Compare →
Anomalo37 of 922Not among the top eight
Ataccama ONE21 of 923Not among the top eight
Informatica Intelligent Data Management Cloud21 of 923Not among the top eight
Acceldata19 of 921Not among the top eight
Collibra Data Quality & Observability19 of 920Not 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 Great Expectations. 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 81 of the 92 answers that named Great Expectations and are not a share of its labels.

Domains cited

atlan.com47
g2.com35
datamation.com32
metaplane.dev29
learn.g2.com24
basedash.com21
airbyte.com20
digna.ai20
guideflow.com20
ovaledge.com19

267 of the 267 domain citations in answers naming Great Expectations came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Search and answers

greatexpectations.io is not in Google's top ten for any of the category's searches. In the answers, Great Expectations takes 2% of first choices and Metaplane takes 31%.
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In search

Google, US estimates
Position for “data observability platform”
–
not in the top ten
Position for “best data observability platform”
–
not in the top ten
Searches for its name, Google
60,500 a month (“great expectations”)
AI search demand for its name, est.
4,980 a month
Organic visits to its site
about 793 a month
Searches its site ranks for
803 · 26 in the top three
Sites linking to it
2,003
Paid Google search
No ads found in the estimate; that does not mean it runs none
Ads on GoogleDetailLess
8 ads · 3 image, 3 text, 2 video · 0 shown in the last 30 days

First shown November 2022, as Great Expectations Labs, Inc., verified. Ads started 2025-11 to 2026-10: 1 in the year, 7 before.

On Google's pages: 1 2 3 4

In answers

This edition
Share of first choices
2%
rank 10 of 110 in data observability
Segment leader
31%
Metaplane
First choices
2 across its categories
Named in
92 answers
Its own site cited
in 81 of the answers that named it

Search figures are US estimates from DataForSEO, read October 5, 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.

What it publishes

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Addresses on greatexpectations.io
1,995
subdomains included
Content
441
counted in the table below
Documentation
85
Product · Integration
0 · 0
KindPagesLast 90 days2025-10 to 2026-09LatestCategories named
Blog243undated
Report or ebook73undated
Glossary or explainer66undated
Case study1802021-03-24
Webinar or virtual event1602021-01-22
Comparison1202026-03-02
Conference or event1112026-08-17
News or press2undated

Most recent

  • 2026-08-172392 conference or event
  • 2026-03-022340 comparison
  • 2025-02-042083 comparison
  • 2024-11-252007 conference or event
  • 2024-10-111945 conference or event
  • 2024-10-081933 comparison
How it is countedHide how it is counted

Every page greatexpectations.io exposes, subdomains included. Kind is read from the address and title. The last 90 days, the latest date and the twelve months count pages by when they were published, from the site's feeds, a date in the address, or the page's own publication date, read from up to a hundred of its most recently changed pages; a page that says only when it last changed is counted in its kind but not in when, so the recent counts are a floor, and a kind none of whose pages gives a publication date reads undated. An event counts as online when its address or title says so (webinar, on demand, virtual or online summit); a conference, summit, trade show, expo or roadshow that does not say so is counted as a conference or event, which on a vendor's site is mostly in person. Read September 29, 2026.

Names read as Great Expectations

What the judge wrote, as written, with how often. The vendor table decides that these count as Great Expectations; a claim can dispute any of them.
Great Expectations (GX) 7Great Expectations (Core) 1Great Expectations (GX Core) 1Great Expectations (OSS Version) 1Great Expectations / GX Core 1

Follow Great Expectations

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.

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The company

Great Expectations is its own company.
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In its own words

Stated by the vendor, not checked
Positioning
GX Core is an open source framework for testing, validating, and documenting data quality across modern data pipelines, workflows, and teams.
For
data practitioners
Free plan or trial
GX Core will always remain free. greatexpectations.io
Integrations claimed
8 greatexpectations.io
Customers named
LOGEXTHINKMDVimeoHeinekenRent the RunwayProvectusAvanadeCalm
Not stated on the pages read
Price, starting price, certifications, hosting

What Great Expectations's own pages state, read October 5, 2026: greatexpectations.io, greatexpectations.io/pricing, greatexpectations.io/security, greatexpectations.io/case-studies, greatexpectations.io/partners. A claimed page can correct any of them.

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 Great Expectations'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 Great Expectations, 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 Great Expectations by email, built from the raw record of the edition. It shows:

  • where Great Expectations 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 Great Expectations, 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.
The subscriber app

A verification link goes to your work email; an address at greatexpectations.io is approved on the spot, any other is reviewed by hand. Your email is never published. Claiming gives no say over labels, shares, verdicts or which quotes appear.