Small business=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 11 pointsRank 23 → 27 of 29
1 category · RankedZilliz Cloud
30Judge labels
1First choices
5Negative labels
12 / 14Models named it
1Category
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 Vector databases for enterprise buyers
Rank 14 of 44 in the mid-market standing
0 of 14 models made it the first choice on the direct prompt; 0% of its 6 labels there were negative.
By buyer segmentRead the same way at every buyer size.
Small business33 of 36
0%8 labels
under the label threshold
Mid-market14 of 44
0%6 labels
under the label threshold
Enterprise6 of 45
2%16 labels
accepted challenger
In vector databases · 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 Zilliz Cloud 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 |
|---|---|---|---|---|---|---|---|
| Vector databases | Data platform | 0% | 14 of 44 | 0% | 6 | under 10 labels · led by pgvector at 35% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
Movement
Since September 2026, Zilliz Cloud held within the floor in its one category: no change cleared 11 points.
Best category · Vector databases · by segment
Mid-market=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 11 pointsRank 9 → 13 of 35
Enterprise▼−3Since September 2026: 5% → 2%, −3 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
2%from 5% in September 2026
Inside the floor by 8 pointsRank 5 → 6 of 44
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Vector databases | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 9 → 14 of 44 |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions
By model
How each model treated Zilliz Cloud across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.ShowHide
By model
How each model treated Zilliz Cloud across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
ShowHide| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 1 | 0 | 0 | 1 |
| Perplexity Sonar | 0 | 0 | 1 | 0 | 1 |
| Grok 4.20 | 0 | 0 | 0 | 0 | 0 |
| Mistral Small | 0 | 0 | 0 | 0 | 0 |
| DeepSeek V4 Flash | 0 | 1 | 0 | 0 | 1 |
| Llama 4 Maverick | 0 | 0 | 1 | 0 | 1 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 0 | 0 |
| Kimi K2 | 0 | 0 | 1 | 0 | 1 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 1 | 0 | 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
Direct4 labelsNone
Paraphrase4 labelsNone
Comparative5 labelsNone
Budget-constrained3 labels1
Scale-constrained6 labelsNone
Negative8 labelsNone
First choiceAlternativeMentionNegative30 labels in all, every segment counted; 1 of the 1 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.
“If you want Milvus's power without the headache, you should look at their managed service, Zilliz Cloud, instead” Gemini 3.5 Flash · Vector databases · negative prompt · alternative
“100M–Billions → Milvus/Zilliz, Pinecone Serverless are the real choices” DeepSeek V4 Flash · Vector databases · scale prompt · alternative
“Zilliz is a managed cloud service on the open-source Milvus engine” Muse Glimmer 30B · Vector databases · 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.
No model argued against it.
Named alongside
The products named in the same answers as Zilliz Cloud, over the 30 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Zilliz Cloud was named but was not.ShowHide
Named alongside
The products named in the same answers as Zilliz Cloud, over the 30 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Zilliz Cloud was named but was not.
ShowHideProductSame answerTook the first choice insteadHead to head
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 Zilliz Cloud. 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 28 of the 30 answers that named Zilliz Cloud and are not a share of its labels.
Domains cited
atlan.com16
iternal.ai15
g2.com12
marktechpost.com10
actian.com8
dev.to7
dupple.com7
firecrawl.dev7
groovyweb.co7
altexsoft.com6
Ninety-five of the ninety-five domain citations in answers naming Zilliz Cloud came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
zilliz.com ranks 7 on Google for the category's searches. In the answers, Zilliz Cloud takes 0% of first choices and pgvector takes 35%.ShowHide
Search and answers
zilliz.com ranks 7 on Google for the category's searches. In the answers, Zilliz Cloud takes 0% of first choices and pgvector takes 35%.
ShowHideIn search
Google, US estimatesPosition for “vector database”
7
Position for “vector databases”
–
not in the top ten
- Searches for its name, Google
- 140 a month (“zilliz cloud”)
- AI search demand for its name, est.
- 2 a month
- Organic visits to its site
- about 11,801 a month
- Searches its site ranks for
- 5,010 · 104 in the top three
- Sites linking to it
- 3,733
- Paid Google search
- No ads found in the estimate; that does not mean it runs none
In answers
This editionShare of first choices
0%
rank 14 of 44 in vector databases
Segment leader
35%
pgvector
- First choices
- 1 across its categories
- Named in
- 30 answers
- Its own site cited
- in 28 of the answers that named it
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.
What it publishes
ShowHide
What it publishes
ShowHideAddresses on zilliz.com
43,515
subdomains included
Content
3,385
counted in the table below
Documentation
2,004
Product · Integration
26 · 70
| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Glossary or explainer | 2,199 | 0 | 2026-06-26 | Vector databases, ETL | |
| Blog | 416 | 2 | 2026-07-16 | Vector databases, ETL | |
| Comparison | 405 | undated | Vector databases, Object storage | ||
| Conference or event | 208 | 0 | 2026-06-30 | Vector databases | |
| Case study | 60 | undated | |||
| Webinar or virtual event | 38 | 0 | 2026-05-21 | Vector databases | |
| News or press | 35 | 2 | 2026-08-05 | Vector databases | |
| Report or ebook | 22 | 0 | 2026-05-01 | Vector databases | |
| Template or tool | 1 | undated | |||
| Podcast or video | 1 | 0 | 2022-06-16 |
Most recent
- 2026-08-05Vdbbench cost aware vector database benchmarking news or press
- 2026-08-01Milvus 3 0 lake native vector database news or press
- 2026-07-16Migrate self managed milvus to zilliz cloud blog
- 2026-07-02Build multimodal search 3d assets tripo zilliz cloud blog
- 2026-06-30Databricks data ai summit 2026 data layer conference or event
- 2026-06-29Pr loon lake native storage engine vector ai workloads news or press
Events in person
Last twelve months
- December 5, 2025Milvus 2.6 Training Session at re:Invent 2025 (Session 3 of 3)Las Vegas · took part
- December 4, 2025Milvus 2.6 Training Session at re:Invent 2025 (Session 3 of 3)re:Invent, Las Vegas (full address will be emailed after registration), Las Vegas · took part
- December 3, 2025Milvus 2.6 Training Session at re:Invent 2025 (Session 2 of 3)re:Invent, Las Vegas (full address will be emailed after registration), Las Vegas · took part
- December 2, 2025Milvus 2.6 Training Session at re:Invent 2025 (Session 1 of 3)re:Invent, Las Vegas (full address will be emailed after registration), Las Vegas · took part
As the event pages on zilliz.com state them, read September 28, 2026.
How it is countedHide how it is counted
Every page zilliz.com 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 Zilliz Cloud
What the judge wrote, as written, with how often. The vendor table decides that these count as Zilliz Cloud; a claim can dispute any of them.
Zilliz 4
Follow Zilliz Cloud
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.
The company
Zilliz Cloud is its own company.ShowHide
The company
Zilliz Cloud is its own company.
ShowHideIn its own words
Stated by the vendor, not checked- Positioning
- Fully managed Vector Lakebase services designed for high reliability, performance, and cost efficiency at scale.
- For
- Enterprise AI
- Price stated
- Flexible pricing options for every team on any budget. zilliz.com
- Starting price
- 0 zilliz.com/pricing
- Free plan or trial
- Free TierUnleash Your Imagination with the Power of Managed Milvus. zilliz.com
- Certifications
- SOC 2 Type IIISO/IEC 27001GDPR readyHIPAA-eligibleHIPAA readySOC 2ISO 27001GDPR
- Hosting
- AWSGoogle CloudAzureus-west-2 (Oregon)GCP30+ regions worldwide
- Customers named
- ExaOpenEvidenceFilevineMiniMaxConsensusAirtableRead AIGorgias
- Not stated on the pages read
- Integrations
What Zilliz Cloud's own pages state, read September 28, 2026: zilliz.com, zilliz.com/pricing, zilliz.com/solution/rag, zilliz.com/customers, zilliz.com/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 Zilliz Cloud'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 Zilliz Cloud, 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 Zilliz Cloud by email, built from the raw record of the edition. It shows:
- where Zilliz Cloud 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 Zilliz Cloud, 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.