Reviewed integration platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.
Data integration
Data integration citation share
12 companies ranked by how often their own pages are the source an AI answer cites.
30.0%
Fivetran ranks first
Citation share
12
Companies ranked
Sep 22
Snapshot recorded
2026 · Rotating schedule
30
Answers behind each row
From the OpenAI, Anthropic and Google model APIs
All 12 companies by citation share
Fivetran leads at 30.0%; the middle of the board sits at 6.7%.
- Ahead of second place
- 13.3%
- Held by the top three
- 60%
- Middle of the board
- 6.7%
- Below half the leader
- 10 of 12
Rank, name and citation shareMiddle 6.7%
- 1Fivetran30.0%
- 2Estuary Flow16.7%
- 3Airbyte13.3%
- 4Hevo Data10.0%
- 5Matillion10.0%
- 6Qlik Talend6.7%
- 7Boomi6.7%
- 8SnapLogic3.3%
- 9Hightouch3.3%
- 10Informatica0.0%
- 11MuleSoft0.0%
- 12Census0.0%
The prompt boards are re-run in rotation, about one category a day, so each board refreshes every few weeks and shows the date of its snapshot.
engines: 2 on 7 of 12 rows · 30 checks behind each row · 100% confidence across rows.
| Rank | Name | Citation share | Mention coverage | Share of names | Cited as source | Change | Why |
|---|---|---|---|---|---|---|---|
| 01 | Fivetran | 30.0% | 37.5% · 18 / 48 | 25.35% · 18 / 71 | 30% · 9 / 30 | This rankMy rank | |
| 02 | Estuary Flow | 16.7% | 12.5% · 6 / 48 | 8.45% · 6 / 71 | 16.67% · 5 / 30 | 5 | This rankMy rank |
| 03 | Airbyte | 13.3% | 18.75% · 9 / 48 | 12.68% · 9 / 71 | 13.33% · 4 / 30 | This rankMy rank | |
| 04 | Hevo Data | 10.0% | 14.58% · 7 / 48 | 9.86% · 7 / 71 | 10% · 3 / 30 | 5 | This rankMy rank |
| 05 | Matillion | 10.0% | 12.5% · 6 / 48 | 8.45% · 6 / 71 | 10% · 3 / 30 | 1 | This rankMy rank |
| 06 | Qlik Talend | 6.7% | 20.83% · 10 / 48 | 14.08% · 10 / 71 | 6.67% · 2 / 30 | 2 | This rankMy rank |
| 07 | Boomi | 6.7% | 6.25% · 3 / 48 | 4.23% · 3 / 71 | 6.67% · 2 / 30 | 5 | This rankMy rank |
| 08 | SnapLogic | 3.3% | 4.17% · 2 / 48 | 2.82% · 2 / 71 | 3.33% · 1 / 30 | 3 | This rankMy rank |
| 09 | Hightouch | 3.3% | 2.08% · 1 / 48 | 1.41% · 1 / 71 | 3.33% · 1 / 30 | 2 | This rankMy rank |
| 10 | Informatica | 0.0% | 10.42% · 5 / 48 | 7.04% · 5 / 71 | 0% · 0 / 30 | 2 | This rankMy rank |
| 11 | MuleSoft | 0.0% | 8.33% · 4 / 48 | 5.63% · 4 / 71 | 0% · 0 / 30 | 1 | ShowingMy rank |
| 12 | Census | 0.0% | 0% · 0 / 48 | 0% · 0 / 71 | 0% · 0 / 30 | 2 | This rankMy rank |
Compare brands
One brand against up to three competitors, answer by answer
16 questions × 3 model APIs · recorded Sep 22, 2026
Compared 4 of 4
37.5%
of these answers name or cite Fivetran
18 of 48 answers
47.4%
Its share of the compared brands' appearances
9
Answers citing its own site
9 links to its domains
3 of 3
Model APIs that name it
| Brand | Named or cited | Against primary | Share of compared | Mentions | Answers citing it | Links to its site | Model APIs |
|---|---|---|---|---|---|---|---|
| Fivetranfivetran.com | 37.5%18 of 48 | Primary | 47.4% | 33 | 9 | 9 | 3 of 3 |
| Airbyteairbyte.com | 18.8%9 of 48 | -18.8 pts | 23.7% | 14 | 3 | 4 | 3 of 3 |
| Matillionmatillion.com | 12.5%6 of 48 | -25.0 pts | 15.8% | 6 | 3 | 3 | 2 of 3 |
| Informaticainformatica.com | 10.4%5 of 48 | -27.1 pts | 13.2% | 9 | 0 | 0 | 2 of 3 |
Every answer
Which compared brands each answer names
16 questions · 48 answers · a blank cell names none of the compared brands
| Question | OpenAIopenai/gpt-4o-mini | Anthropicanthropic/claude-haiku-4-5 | Geminigoogle/gemini-2.5-flash |
|---|---|---|---|
| 01Which managed data integration platforms are best for loading many SaaS and database sources into a cloud warehouse?Recommendation | Fivetran, cited 1InformaticaMatillion 6 sources 57db4743 | None named 0 sources 509db2de | Fivetran, cited 1Matillion 8 sources 748686bd |
| 02Recommend a self-hostable data integration platform with broad connectors, orchestration, observability, and extensibility.Recommendation | Airbyte, cited 2 4 sources f0d6a9d6 | Airbyte 0 sources d4385c12 | Airbyte 4 sources ab12b042 |
| 03Which data integration tools are strongest for reliable low-latency change data capture from operational databases?Recommendation | Fivetran, cited 1 4 sources 45b56c62 | None named 0 sources 01d0b960 | FivetranAirbyte, cited 1 6 sources 5e4e6142 |
| 04Recommend a platform for syncing governed warehouse data into sales, marketing, support, and advertising applications.Recommendation | None named 8 sources 57c63476 | None named 0 sources f472e688 | Fivetran 5 sources c66d38b1 |
| 05Which data integration platforms best support enterprise governance, lineage, private networking, auditability, and role control?Recommendation | FivetranInformatica 5 sources a2721cfe | None named 0 sources 9890fbff | FivetranAirbyteInformatica 8 sources 90a93215 |
| 06Recommend a data pipeline service with dependable managed connectors for finance, CRM, advertising, support, and product analytics.Recommendation | Fivetran, cited 1Airbyte, cited 1Matillion 4 sources 43a6d146 | Fivetran 0 sources 56b17802 | Fivetran, cited 1Airbyte 8 sources 2a634a46 |
| 07Which data integration platform works best with modular SQL transformation, workflow orchestration, testing, and warehouse-native execution?Recommendation | Fivetran 5 sources 74279bf6 | None named 5 sources e99a41d0 | None named 4 sources e627b6aa |
| 08What data integration tool should a startup evaluate for fast setup, predictable cost, common connectors, and low maintenance?Recommendation | Fivetran 8 sources a5683d6a | None named 0 sources be73f0df | FivetranAirbyte 7 sources 9e21352b |
| 09Compare data integration platforms on connector coverage, freshness, reliability, observability, governance, deployment, and support.Commercial comparison | FivetranAirbyteInformatica 5 sources 1cc08992 | None named 0 sources 9d445e7a | Fivetran, cited 1 7 sources 20475281 |
| 10How should a buyer compare data integration pricing across rows, active records, compute, connectors, and platform fees?Commercial comparison | None named 5 sources 86c245f5 | None named 0 sources 7e9e5fbb | None named 6 sources f1204240 |
| 11Create a proof-of-concept scorecard for measuring pipeline freshness, recovery, data loss, duplicate handling, and support quality.Commercial comparison | None named 0 sources 077dfa81 | None named 2 sources 80eb9d04 | None named 3 sources 0083aaa6 |
| 12Compare how data integration tools handle schema drift, connector changes, backfills, replay, and destination compatibility.Commercial comparison | Fivetran, cited 1 7 sources 8b077e51 | None named 0 sources 1edde5ce | None named 9 sources 2a0d4eb6 |
| 13Which criteria expose lock-in and migration risk when choosing a managed data integration platform?Commercial comparison | None named 9 sources d377870e | None named 0 sources c73b6593 | None named 8 sources 22643966 |
| 14Compare data pipeline vendors on encryption, secrets, private connectivity, data residency, compliance, and customer-managed deployment.Commercial comparison | None named 7 sources bc43e3db | None named 0 sources a978dcdc | Matillion, cited 1 2 sources f538bcac |
| 15Create a shortlist of data integration vendors for a global enterprise modernizing batch, streaming, and activation pipelines.Commercial comparison | Fivetran, cited 1Matillion, cited 1 7 sources 9636b035 | None named 0 sources 452d3cee | Fivetran, cited 1Informatica 6 sources 9456aac7 |
| 16When should a company consolidate ingestion, transformation, quality, observability, and activation on one data integration platform?Commercial comparison | None named 9 sources 709012ea | None named 0 sources 80572b06 | Matillion, cited 1 6 sources 20eb5a04 |
Sources
The sites these answers cite
Each site is read from the cited address itself.
| Site | Answers citing it | Distinct pages | Model APIs | Best position |
|---|---|---|---|---|
| domo.com | 14 | 7 | 2 | 1 |
| integrate.io | 11 | 9 | 2 | 1 |
| skyvia.com | 10 | 5 | 2 | 1 |
| fivetran.com | 9 | 5 | 2 | 1 |
| estuary.dev | 5 | 4 | 2 | 3 |
| improvado.io | 5 | 3 | 2 | 2 |
| striim.com | 4 | 4 | 2 | 2 |
| gartner.com | 4 | 2 | 2 | 1 |
| stacksync.com | 4 | 2 | 2 | 1 |
| airbyte.com | 3 | 4 | 2 | 2 |
| bladepipe.com | 3 | 3 | 2 | 1 |
| matillion.com | 3 | 3 | 2 | 1 |
| reddit.com | 3 | 3 | 1 | 1 |
| hevodata.com | 3 | 3 | 2 | 2 |
| nexla.com | 3 | 3 | 2 | 2 |
| linkedin.com | 3 | 2 | 2 | 1 |
| peliqan.io | 3 | 1 | 2 | 3 |
| salesforce.com | 2 | 2 | 2 | 1 |
| streamkap.com | 2 | 2 | 2 | 1 |
| boomi.com | 2 | 2 | 2 | 2 |
What this report publishesThe public buying questions, the brands each answer names, the sources it cites and a fingerprint of each answer. Answer text is not published, and no customer data is in it.data-integration-platforms-2026-07-27 / 4-data-integration-platforms-2026-07-27-models-64232fd32583
Why this rank
MuleSoft on Data Integration Citation Share
Snapshot of Sep 22, 2026, 12:00 AM UTC · Link to this snapshot
Ranks a reviewed Data Integration brand universe using a fixed, public set of neutral commercial prompts across 3 AI providers.
11
Rank on this board
0 percent
Score
30
Answers behind the score
100% confidence · 1 of 1 components evidenced
What the score is built from
1 of 1 evidencedEvery component evidenced · 1 evidence record each
| Component | Value | Contribution |
|---|---|---|
| Citation share | 0 | 0 |
Moved up since the previous snapshot
+1 places- Gemini brand mention coverage0 to 12.5+12.5
- Gemini brand recommendation presence0 to 12.5+12.5
- OpenAI brand mention coverage0 to 12.5+12.5
- OpenAI brand recommendation presence0 to 12.5+12.5
- Mention coverage0 to 8.333+8.333
- Recommendation presence0 to 8.333+8.333
- Mention share0 to 5.634+5.634
- Engine breadth0 to 2+2
- Anthropic brand mention coverage0 to 00
- Anthropic brand recommendation presence0 to 00
- Citation share0 to 00
- Gemini brand citation share0 to 00
- OpenAI brand citation share0 to 00
Where each number comes from
13 public recordsAnthropic mention coverageAnthropic brand mention coverage · observed Sep 22, 2026, 12:00 AM UTC0 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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Anthropic recommendation-prompt presenceAnthropic brand recommendation presence · observed Sep 22, 2026, 12:00 AM UTC0 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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Citation shareCitation share · observed Sep 22, 2026, 12:00 AM UTC0 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
{"corpusVersion":"data-integration-platforms-2026-07-27","runArtifactIds":["7ce7c4bd-4951-443d-87a4-34707db586bb","f93f176f-5c88-4116-991a-976c8a62aade","24f5964f-bd26-43c4-b39f-7321214dc87c","877df6fd-4fe4-4218-ad4a-b062f9b2243d","a3491061-2e9f-4950-b9b0-b22d5045ea8b","355997c8-c95f-4f90-a8d1-892e532d5076","82bb7da5-36f9-4d8a-a980-d4ed27d3d062","e481535f-b02a-456f-a4df-c5914f65c14d","1af7065b-2487-402e-b884-2cb7fbfdd313","019709d6-25bd-4000-988a-b4588b4e2ba5","169a85f4-d55a-40ae-813a-bb02e61d920e","e465dbbc-2f69-4bc9-89a0-8507d6f42c84","8cd16adc-b811-44e5-a7d4-8060004ded0c","c0b8b8c4-d3f7-45cc-bdef-e06ff9c643c1","6a60171b-77ff-4cfd-b5b0-6c73d29f85b5","89811e81-3d66-46df-866f-35f3a797c861","63897b24-cc86-4efc-b5b3-90b62257a5b1","62295d9e-31ea-47ba-9801-e9aef566c308","251ca83f-e0cf-4d48-80f4-47069f1eac4b","f8a71c95-7155-4b0b-a624-0449580dc2f4","5b4004b3-9d5d-4b55-9d39-dfc0ba9f3af9","0e9e9191-e1a7-4d47-b592-1c6d159b9089","fe29cd73-e0b1-4581-8922-8e262293f6df","228b0773-ffa1-41b0-8b52-a031ec6dd57a","fb3b81e9-9242-4f57-9d64-acbc0c350e4b","aaf86a5d-af65-4839-a7c8-6bf62af069d8","bd2351cd-22a1-48dd-a3d6-878f4f0598dc","710819c0-f258-41de-aa65-03ee3a80a3ea","ef164e28-6cfc-4bc2-8096-fabbf143bc6f","f82d658d-a3f0-4929-9ab6-81d7e73cc97d","3601253b-2dcd-4d91-abbe-d76a68ad21e2","cbcadb32-8c9f-4134-9076-abc2b993a55e","f2b33f07-a6b4-4edb-a291-924b8430390c","c77c5810-2b89-45fe-9a4d-64fdb0456f45","e9a96b4e-f4a1-40f2-a184-9ff0b397bcda","e69ceb6a-00e8-487c-9dad-791ec7db1fab","091ff6fe-b848-413e-b54a-db2268dea07f","b70c45d6-68c3-423c-b9bb-95fec9b3c804","8ce1560e-ba6f-4978-8b36-d0151674d901","bd7aa6c0-7b9a-474a-9bc3-a3cde122a5d8","37076ce0-2f00-48d6-b7fe-d433e79b5d50","31342e7c-71dc-4ee6-97b7-9e439846de2f","811caa35-c802-465e-ae82-71799d42ac39","eaf9c5a1-c453-4331-bbd0-ff1ca1487adb","1987e9a8-e750-4860-8a76-238cdae27b14","1ba7ab34-36f4-4996-b894-4854d89755b0","9d667376-0ace-4049-8463-3988e351e41b","4837c5a2-c74e-4a7f-84ae-a1906fe91563"],"benchmarkVersion":"4-data-integration-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Engine breadthEngine breadth · observed Sep 22, 2026, 12:00 AM UTC2 engines100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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Mention coverageMention coverage · observed Sep 22, 2026, 12:00 AM UTC8.333 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
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Reviewed-brand presence shareMention share · observed Sep 22, 2026, 12:00 AM UTC5.634 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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Recommendation-prompt presenceRecommendation presence · observed Sep 22, 2026, 12:00 AM UTC8.333 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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Gemini citation shareGemini brand citation share · observed Sep 22, 2026, 12:00 AM UTC0 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
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Gemini mention coverageGemini brand mention coverage · observed Sep 22, 2026, 12:00 AM UTC12.5 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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Gemini recommendation-prompt presenceGemini brand recommendation presence · observed Sep 22, 2026, 12:00 AM UTC12.5 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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OpenAI citation shareOpenAI brand citation share · observed Sep 22, 2026, 12:00 AM UTC0 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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OpenAI mention coverageOpenAI brand mention coverage · observed Sep 22, 2026, 12:00 AM UTC12.5 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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OpenAI recommendation-prompt presenceOpenAI brand recommendation presence · observed Sep 22, 2026, 12:00 AM UTC12.5 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
{"corpusVersion":"data-integration-platforms-2026-07-27","runArtifactIds":["7ce7c4bd-4951-443d-87a4-34707db586bb","f93f176f-5c88-4116-991a-976c8a62aade","24f5964f-bd26-43c4-b39f-7321214dc87c","877df6fd-4fe4-4218-ad4a-b062f9b2243d","a3491061-2e9f-4950-b9b0-b22d5045ea8b","355997c8-c95f-4f90-a8d1-892e532d5076","82bb7da5-36f9-4d8a-a980-d4ed27d3d062","e481535f-b02a-456f-a4df-c5914f65c14d","1af7065b-2487-402e-b884-2cb7fbfdd313","019709d6-25bd-4000-988a-b4588b4e2ba5","169a85f4-d55a-40ae-813a-bb02e61d920e","e465dbbc-2f69-4bc9-89a0-8507d6f42c84","8cd16adc-b811-44e5-a7d4-8060004ded0c","c0b8b8c4-d3f7-45cc-bdef-e06ff9c643c1","6a60171b-77ff-4cfd-b5b0-6c73d29f85b5","89811e81-3d66-46df-866f-35f3a797c861","63897b24-cc86-4efc-b5b3-90b62257a5b1","62295d9e-31ea-47ba-9801-e9aef566c308","251ca83f-e0cf-4d48-80f4-47069f1eac4b","f8a71c95-7155-4b0b-a624-0449580dc2f4","5b4004b3-9d5d-4b55-9d39-dfc0ba9f3af9","0e9e9191-e1a7-4d47-b592-1c6d159b9089","fe29cd73-e0b1-4581-8922-8e262293f6df","228b0773-ffa1-41b0-8b52-a031ec6dd57a","fb3b81e9-9242-4f57-9d64-acbc0c350e4b","aaf86a5d-af65-4839-a7c8-6bf62af069d8","bd2351cd-22a1-48dd-a3d6-878f4f0598dc","710819c0-f258-41de-aa65-03ee3a80a3ea","ef164e28-6cfc-4bc2-8096-fabbf143bc6f","f82d658d-a3f0-4929-9ab6-81d7e73cc97d","3601253b-2dcd-4d91-abbe-d76a68ad21e2","cbcadb32-8c9f-4134-9076-abc2b993a55e","f2b33f07-a6b4-4edb-a291-924b8430390c","c77c5810-2b89-45fe-9a4d-64fdb0456f45","e9a96b4e-f4a1-40f2-a184-9ff0b397bcda","e69ceb6a-00e8-487c-9dad-791ec7db1fab","091ff6fe-b848-413e-b54a-db2268dea07f","b70c45d6-68c3-423c-b9bb-95fec9b3c804","8ce1560e-ba6f-4978-8b36-d0151674d901","bd7aa6c0-7b9a-474a-9bc3-a3cde122a5d8","37076ce0-2f00-48d6-b7fe-d433e79b5d50","31342e7c-71dc-4ee6-97b7-9e439846de2f","811caa35-c802-465e-ae82-71799d42ac39","eaf9c5a1-c453-4331-bbd0-ff1ca1487adb","1987e9a8-e750-4860-8a76-238cdae27b14","1ba7ab34-36f4-4996-b894-4854d89755b0","9d667376-0ace-4049-8463-3988e351e41b","4837c5a2-c74e-4a7f-84ae-a1906fe91563"],"benchmarkVersion":"4-data-integration-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
More in Data integration
Ingestion, ELT, CDC, integration, and data activation platforms ranked across a fixed enterprise buying corpus.
Reviewed vendors ranked by the share of all the category's answers that name or cite them.
Reviewed vendors ranked by how many of the three model APIs name or cite them.
See how often AI names you.
Enter your website. In about two minutes, Rank.ai asks ChatGPT, Claude and Gemini 12 questions your customers ask and grades how often they name you.
- Your grade out of 100How often AI names you, cites your site, and how high it ranks you.
- Who gets namedEvery competitor in the answers, most named first.
- The pages AI readsThe sources behind each answer.
- Three fixesWhat to fix first, with a brief for the first article.