Data platform presence

As of

All 16 companies by mention coverage

Databricks leads at 27.8%; the middle of the board sits at 8.3%.

Ahead of second place: 2.8%
Held by the top three: 43%
Middle of the board: 8.3%
Below half the leader: 10 of 16

Rank, name and mention coverageMiddle 8.3%

1Databricks27.8%
2Google BigQuery25.0%
3MotherDuck22.2%
4Amazon Redshift22.2%
5Snowflake22.2%
6Dremio13.9%
7Confluent8.3%
8ClickHouse Cloud8.3%
9Microsoft Fabric8.3%
10Teradata VantageCloud5.6%
11Cloudera2.8%
12Firebolt2.8%
13SingleStore2.8%
14Oracle Autonomous Database2.8%
15MongoDB Atlas0.0%
16Starburst0.0%

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.

chatgpt cites it: 6.666667 on 7 of 16 rows · 36 checks behind each row · 100% confidence across rows.

Data platforms brand visibility current rankings
Rank	Name	Mention coverage	Share of names	Cited as source	Engines	Change	Why
01	Databricks	27.8%	15.87% · 10 / 63	17.65% · 6 / 34	2	1	This rank My rank
02	Google BigQuery	25.0%	14.29% · 9 / 63	2.94% · 1 / 34	3	1	This rank My rank
03	MotherDuck	22.2%	12.7% · 8 / 63	14.71% · 5 / 34	3	2	This rank My rank
04	Amazon Redshift	22.2%	12.7% · 8 / 63	8.82% · 3 / 34	2	2	This rank My rank
05	Snowflake	22.2%	12.7% · 8 / 63	8.82% · 3 / 34	3	1	This rank My rank
06	Dremio	13.9%	7.94% · 5 / 63	14.71% · 5 / 34	2	5	This rank My rank
07	Confluent	8.3%	4.76% · 3 / 63	5.88% · 2 / 34	3		This rank My rank
08	ClickHouse Cloud	8.3%	4.76% · 3 / 63	2.94% · 1 / 34	2	7	This rank My rank
09	Microsoft Fabric	8.3%	4.76% · 3 / 63	5.88% · 2 / 34	2	5	This rank My rank
10	Teradata VantageCloud	5.6%	3.17% · 2 / 63	5.88% · 2 / 34	2	2	This rank My rank
11	Cloudera	2.8%	1.59% · 1 / 63	2.94% · 1 / 34	1		Showing My rank
12	Firebolt	2.8%	1.59% · 1 / 63	2.94% · 1 / 34	1	2	This rank My rank
13	SingleStore	2.8%	1.59% · 1 / 63	2.94% · 1 / 34	1		This rank My rank
14	Oracle Autonomous Database	2.8%	1.59% · 1 / 63	2.94% · 1 / 34	1	2	This rank My rank
15	MongoDB Atlas	0.0%	0% · 0 / 63	0% · 0 / 34	0	1	This rank My rank
16	Starburst	0.0%	0% · 0 / 63	0% · 0 / 34	0	7	This rank My rank

chatgpt cites it: 6.666667 on 7 of 16 rows · 36 checks behind each row · 100% confidence across rows.

Data platforms brand visibility current rankings
Rank	Name	Mention coverage	Share of names	Cited as source	Engines	Change	Why
01	Databricks	27.8%	15.87% · 10 / 63	17.65% · 6 / 34	2	1	This rank My rank
02	Google BigQuery	25.0%	14.29% · 9 / 63	2.94% · 1 / 34	3	1	This rank My rank
03	MotherDuck	22.2%	12.7% · 8 / 63	14.71% · 5 / 34	3	2	This rank My rank
04	Amazon Redshift	22.2%	12.7% · 8 / 63	8.82% · 3 / 34	2	2	This rank My rank
05	Snowflake	22.2%	12.7% · 8 / 63	8.82% · 3 / 34	3	1	This rank My rank
06	Dremio	13.9%	7.94% · 5 / 63	14.71% · 5 / 34	2	5	This rank My rank
07	Confluent	8.3%	4.76% · 3 / 63	5.88% · 2 / 34	3		This rank My rank
08	ClickHouse Cloud	8.3%	4.76% · 3 / 63	2.94% · 1 / 34	2	7	This rank My rank
09	Microsoft Fabric	8.3%	4.76% · 3 / 63	5.88% · 2 / 34	2	5	This rank My rank
10	Teradata VantageCloud	5.6%	3.17% · 2 / 63	5.88% · 2 / 34	2	2	This rank My rank
11	Cloudera	2.8%	1.59% · 1 / 63	2.94% · 1 / 34	1		Showing My rank
12	Firebolt	2.8%	1.59% · 1 / 63	2.94% · 1 / 34	1	2	This rank My rank
13	SingleStore	2.8%	1.59% · 1 / 63	2.94% · 1 / 34	1		This rank My rank
14	Oracle Autonomous Database	2.8%	1.59% · 1 / 63	2.94% · 1 / 34	1	2	This rank My rank
15	MongoDB Atlas	0.0%	0% · 0 / 63	0% · 0 / 34	0	1	This rank My rank
16	Starburst	0.0%	0% · 0 / 63	0% · 0 / 34	0	7	This rank My rank

Primary brandQuestion typeModel APIQuestion contains

Run a question live

22.2%

of these answers name or cite Snowflake

8 of 36 answers

22.9%

Its share of the compared brands' appearances

1

Answers citing its own site

3 links to its domains

3 of 3

Model APIs that name it

The compared brands across the filtered answers
Brand	Named or cited	Against primary	Share of compared	Mentions	Answers citing it	Links to its site	Model APIs
Databricksdatabricks.com	27.8%10 of 36	+5.6 pts	28.6%	18	6	6	2 of 3
Google BigQuerycloud.google.com	25.0%9 of 36	+2.8 pts	25.7%	17	1	1	3 of 3
Amazon Redshiftaws.amazon.com	22.2%8 of 36	0.0 pts	22.9%	8	3	3	2 of 3
Snowflakesnowflake.com	22.2%8 of 36	Primary	22.9%	19	1	3	3 of 3

Compared brands named in each answer, by question and model API
Question	OpenAIopenai/gpt-4o-mini	Anthropicanthropic/claude-haiku-4-5	Geminigoogle/gemini-2.5-flash
01Which cloud data platforms are best for a global enterprise that needs high-concurrency analytics, workload isolation, governance, and predictable performance?Recommendation	Snowflake, cited 3DatabricksGoogle BigQueryAmazon Redshift 5 sources`d3bf4f82`	None named 0 sources`05a6775c`	SnowflakeGoogle BigQueryAmazon Redshift 8 sources`5c2110ca`
02Recommend a data lakehouse for analytics, machine learning, generative AI, open data formats, notebooks, and production model workflows.Recommendation	SnowflakeDatabricks, cited 1 8 sources`fe11be1c`	None named 0 sources`9f7c1f69`	DatabricksGoogle BigQuery, cited 1 9 sources`7f483494`
03Which serverless data warehouse is best for bursty workloads, minimal administration, elastic scaling, and usage-based pricing?Recommendation	Databricks, cited 1Google BigQueryAmazon Redshift 6 sources`2389d440`	None named 0 sources`e4036521`	Databricks, cited 1Amazon Redshift, cited 1 9 sources`1d14962e`
04Recommend a platform for real-time event streaming, stream processing, low-latency analytics, data contracts, and operational reliability.Recommendation	None named 6 sources`b19498d3`	None named 0 sources`7359a238`	Databricks, cited 1Amazon Redshift, cited 1 10 sources`4ea53c82`
05Which data platforms work best with open table formats and object storage while preserving interoperability, catalog governance, and query performance?Recommendation	None named 7 sources`5cd5eae3`	None named 0 sources`bacbe394`	Databricks, cited 1 9 sources`37a49ad0`
06Recommend a data platform for operational AI applications that need fresh application data, vector search, transactions, and low-latency serving.Recommendation	Amazon Redshift, cited 1 7 sources`c8ea8e7f`	None named 0 sources`e10b0802`	None named 9 sources`60a7f3c3`
07Which data platform is strongest for multi-cloud governance, fine-grained access control, lineage, data sharing, privacy, and regulatory compliance?Recommendation	None named 6 sources`77b8d251`	None named 0 sources`b3dd0bc3`	Databricks, cited 1 9 sources`cb62ce33`
08What data platform should a startup or small analytics team choose for fast setup, simple operations, familiar SQL, and controlled early-stage cost?Recommendation	Google BigQuery 7 sources`509e84aa`	Snowflake 0 sources`c8246fb4`	SnowflakeGoogle BigQueryAmazon Redshift 5 sources`16aa7c7e`
09Compare modern data platforms on performance, concurrency, openness, governance, developer experience, AI readiness, reliability, and ecosystem depth.Commercial comparison	SnowflakeDatabricksGoogle BigQueryAmazon Redshift 3 sources`78aa81ad`	None named 0 sources`c9123048`	SnowflakeDatabricksGoogle BigQuery 0 sources`0326bddb`
10How should a buyer compare data-platform total cost across storage, compute, data movement, concurrency, idle capacity, support, and administration?Commercial comparison	None named 7 sources`02225812`	None named 0 sources`a3d1b880`	None named 8 sources`e2211b43`
11Create a proof-of-concept scorecard for data platforms using ingestion, transformation, mixed queries, governance, recovery, and cost-control tests.Commercial comparison	None named 0 sources`9db2a35f`	SnowflakeGoogle BigQuery 0 sources`be458853`	None named 0 sources`3337e223`
12Which criteria expose data-platform migration complexity, egress cost, proprietary interfaces, skills risk, workload portability, and vendor lock-in?Commercial comparison	None named 7 sources`99d4b872`	None named 0 sources`ea066f48`	None named 4 sources`268855ca`

Sites cited in the filtered answers
Site	Answers citing it	Distinct pages	Model APIs	Best position
youtube.com	8	7	2	1
reddit.com	6	6	2	1
motherduck.com	5	5	2	2
dremio.com	5	4	2	2
databricks.com	4	4	2	1
ibm.com	4	4	2	1
rank.ai	4	4	2	1
linkedin.com	3	3	2	1
medium.com	3	3	1	2
ovaledge.com	3	3	2	3
arxiv.org	2	2	2	1
striim.com	2	2	2	1
aws.amazon.com	2	2	2	2
confluent.io	2	2	2	2
couchbase.com	2	2	1	2
montecarlo.ai	2	2	2	2
lumenalta.com	2	2	2	4
athena-solutions.com	2	2	2	5
gartner.com	2	2	2	5
domo.com	2	2	2	6

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-platforms-2026-07-27 / 4-data-platforms-2026-07-27-models-64232fd32583

Primary brandQuestion typeModel APIQuestion contains

Run a question live

22.2%

of these answers name or cite Snowflake

8 of 36 answers

22.9%

Its share of the compared brands' appearances

1

Answers citing its own site

3 links to its domains

3 of 3

Model APIs that name it

The compared brands across the filtered answers
Brand	Named or cited	Against primary	Share of compared	Mentions	Answers citing it	Links to its site	Model APIs
Databricksdatabricks.com	27.8%10 of 36	+5.6 pts	28.6%	18	6	6	2 of 3
Google BigQuerycloud.google.com	25.0%9 of 36	+2.8 pts	25.7%	17	1	1	3 of 3
Amazon Redshiftaws.amazon.com	22.2%8 of 36	0.0 pts	22.9%	8	3	3	2 of 3
Snowflakesnowflake.com	22.2%8 of 36	Primary	22.9%	19	1	3	3 of 3

Compared brands named in each answer, by question and model API
Question	OpenAIopenai/gpt-4o-mini	Anthropicanthropic/claude-haiku-4-5	Geminigoogle/gemini-2.5-flash
01Which cloud data platforms are best for a global enterprise that needs high-concurrency analytics, workload isolation, governance, and predictable performance?Recommendation	Snowflake, cited 3DatabricksGoogle BigQueryAmazon Redshift 5 sources`d3bf4f82`	None named 0 sources`05a6775c`	SnowflakeGoogle BigQueryAmazon Redshift 8 sources`5c2110ca`
02Recommend a data lakehouse for analytics, machine learning, generative AI, open data formats, notebooks, and production model workflows.Recommendation	SnowflakeDatabricks, cited 1 8 sources`fe11be1c`	None named 0 sources`9f7c1f69`	DatabricksGoogle BigQuery, cited 1 9 sources`7f483494`
03Which serverless data warehouse is best for bursty workloads, minimal administration, elastic scaling, and usage-based pricing?Recommendation	Databricks, cited 1Google BigQueryAmazon Redshift 6 sources`2389d440`	None named 0 sources`e4036521`	Databricks, cited 1Amazon Redshift, cited 1 9 sources`1d14962e`
04Recommend a platform for real-time event streaming, stream processing, low-latency analytics, data contracts, and operational reliability.Recommendation	None named 6 sources`b19498d3`	None named 0 sources`7359a238`	Databricks, cited 1Amazon Redshift, cited 1 10 sources`4ea53c82`
05Which data platforms work best with open table formats and object storage while preserving interoperability, catalog governance, and query performance?Recommendation	None named 7 sources`5cd5eae3`	None named 0 sources`bacbe394`	Databricks, cited 1 9 sources`37a49ad0`
06Recommend a data platform for operational AI applications that need fresh application data, vector search, transactions, and low-latency serving.Recommendation	Amazon Redshift, cited 1 7 sources`c8ea8e7f`	None named 0 sources`e10b0802`	None named 9 sources`60a7f3c3`
07Which data platform is strongest for multi-cloud governance, fine-grained access control, lineage, data sharing, privacy, and regulatory compliance?Recommendation	None named 6 sources`77b8d251`	None named 0 sources`b3dd0bc3`	Databricks, cited 1 9 sources`cb62ce33`
08What data platform should a startup or small analytics team choose for fast setup, simple operations, familiar SQL, and controlled early-stage cost?Recommendation	Google BigQuery 7 sources`509e84aa`	Snowflake 0 sources`c8246fb4`	SnowflakeGoogle BigQueryAmazon Redshift 5 sources`16aa7c7e`
09Compare modern data platforms on performance, concurrency, openness, governance, developer experience, AI readiness, reliability, and ecosystem depth.Commercial comparison	SnowflakeDatabricksGoogle BigQueryAmazon Redshift 3 sources`78aa81ad`	None named 0 sources`c9123048`	SnowflakeDatabricksGoogle BigQuery 0 sources`0326bddb`
10How should a buyer compare data-platform total cost across storage, compute, data movement, concurrency, idle capacity, support, and administration?Commercial comparison	None named 7 sources`02225812`	None named 0 sources`a3d1b880`	None named 8 sources`e2211b43`
11Create a proof-of-concept scorecard for data platforms using ingestion, transformation, mixed queries, governance, recovery, and cost-control tests.Commercial comparison	None named 0 sources`9db2a35f`	SnowflakeGoogle BigQuery 0 sources`be458853`	None named 0 sources`3337e223`
12Which criteria expose data-platform migration complexity, egress cost, proprietary interfaces, skills risk, workload portability, and vendor lock-in?Commercial comparison	None named 7 sources`99d4b872`	None named 0 sources`ea066f48`	None named 4 sources`268855ca`

Sites cited in the filtered answers
Site	Answers citing it	Distinct pages	Model APIs	Best position
youtube.com	8	7	2	1
reddit.com	6	6	2	1
motherduck.com	5	5	2	2
dremio.com	5	4	2	2
databricks.com	4	4	2	1
ibm.com	4	4	2	1
rank.ai	4	4	2	1
linkedin.com	3	3	2	1
medium.com	3	3	1	2
ovaledge.com	3	3	2	3
arxiv.org	2	2	2	1
striim.com	2	2	2	1
aws.amazon.com	2	2	2	2
confluent.io	2	2	2	2
couchbase.com	2	2	1	2
montecarlo.ai	2	2	2	2
lumenalta.com	2	2	2	4
athena-solutions.com	2	2	2	5
gartner.com	2	2	2	5
domo.com	2	2	2	6

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-platforms-2026-07-27 / 4-data-platforms-2026-07-27-models-64232fd32583

Ranks a reviewed Data Platforms brand universe using a fixed, public set of neutral commercial prompts across 3 AI providers.

11

Rank on this board

2.778 percent

Score

36

Answers behind the score

100% confidence · 1 of 1 components evidenced

What the score is built from

1 of 1 evidenced

Every component evidenced · 1 evidence record each

Components of Cloudera's score
Component	Value	Contribution
Mention coverage	2.777778	2.778

Unchanged since the previous snapshot

No change in rank

No component moved since the previous snapshot.

Where each number comes from

13 public records

Anthropic mention coverageAnthropic brand mention coverage · observed Sep 20, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Data Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"data-platforms-2026-07-27","runArtifactIds":["360885b6-888c-4b84-b234-d98f3fbb248d","c72e77cb-1a63-447c-8ddb-8a30e3ebeb15","29e083f8-ff77-403d-9fd6-dcb93a67968b","5967da8a-0bb3-4c6f-ac82-cfabf774acc3","1686db53-6be4-4b90-9eb2-3f7df9f68389","3ab75670-79be-492c-8c80-f821ab00da2e","f898d076-6a23-4b06-a14d-de866de2c86d","8e361cdf-daa2-49f0-b643-4a410e8d9ae8","4e012623-ba28-4686-9f7a-34e82b1ea929","0fc840b7-d1d9-4960-a465-9562aaef8e2b","d1e24599-d01f-4cf1-9263-cd5515f38ab5","03f9920c-2ce4-4d67-81d9-05c625ff1862","d4751102-3faa-4eb3-8e1b-47e89eaa9862","20988919-d331-4cb0-aa13-d89105ae8016","d217cf56-b58d-4e4b-abac-50b32e68745f","cad206cd-350f-47d4-b557-57e66c7d5a31","2876054a-d15d-4059-a32c-6ae11c717ae2","19dfa956-fb61-4d80-a20c-1fe42303e16c","692ec6b6-0fd2-4b69-84a5-38cd27799136","7de9d72b-4ee1-404b-870c-063835484001","d02e5cd9-2619-4dc3-9c2a-72770f8e085f","49e1169c-302e-4ba4-bd55-41d52ba81405","9250031e-c201-4d08-97df-6574d8aadc0a","ea86f3b0-b5e5-47cd-9ce2-bddc28493fbc","78b36eae-87c4-4e87-a962-eafe0857dee8","41f14ffa-0bac-41b4-9607-44faa10247f0","5f7cd97b-9ac4-4cee-be99-6f1de1b79cec","2276f5fb-99ae-4ced-b55d-49e19fc85bff","3051fdf0-02e7-45ce-bb05-669043d3f24e","c29edf74-1c49-40c8-883d-2bb5cabfb3c8","75363fb3-42d1-49b3-a5f2-6bfdfe8186f7","39f5fc8b-c9e3-46b8-b73a-f2e293cd0ce7","c9a5dcc9-0dbb-46c0-81eb-228e08235345","8db98431-8234-49e2-a380-d6db57d3f86f","dec78d6b-790f-43a5-94f4-616cebd10345","521e6c4d-b5ac-48c7-ab12-2cdfd7e7032f"],"benchmarkVersion":"4-data-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Anthropic recommendation-prompt presenceAnthropic brand recommendation presence · observed Sep 20, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Data Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"data-platforms-2026-07-27","runArtifactIds":["360885b6-888c-4b84-b234-d98f3fbb248d","c72e77cb-1a63-447c-8ddb-8a30e3ebeb15","29e083f8-ff77-403d-9fd6-dcb93a67968b","5967da8a-0bb3-4c6f-ac82-cfabf774acc3","1686db53-6be4-4b90-9eb2-3f7df9f68389","3ab75670-79be-492c-8c80-f821ab00da2e","f898d076-6a23-4b06-a14d-de866de2c86d","8e361cdf-daa2-49f0-b643-4a410e8d9ae8","4e012623-ba28-4686-9f7a-34e82b1ea929","0fc840b7-d1d9-4960-a465-9562aaef8e2b","d1e24599-d01f-4cf1-9263-cd5515f38ab5","03f9920c-2ce4-4d67-81d9-05c625ff1862","d4751102-3faa-4eb3-8e1b-47e89eaa9862","20988919-d331-4cb0-aa13-d89105ae8016","d217cf56-b58d-4e4b-abac-50b32e68745f","cad206cd-350f-47d4-b557-57e66c7d5a31","2876054a-d15d-4059-a32c-6ae11c717ae2","19dfa956-fb61-4d80-a20c-1fe42303e16c","692ec6b6-0fd2-4b69-84a5-38cd27799136","7de9d72b-4ee1-404b-870c-063835484001","d02e5cd9-2619-4dc3-9c2a-72770f8e085f","49e1169c-302e-4ba4-bd55-41d52ba81405","9250031e-c201-4d08-97df-6574d8aadc0a","ea86f3b0-b5e5-47cd-9ce2-bddc28493fbc","78b36eae-87c4-4e87-a962-eafe0857dee8","41f14ffa-0bac-41b4-9607-44faa10247f0","5f7cd97b-9ac4-4cee-be99-6f1de1b79cec","2276f5fb-99ae-4ced-b55d-49e19fc85bff","3051fdf0-02e7-45ce-bb05-669043d3f24e","c29edf74-1c49-40c8-883d-2bb5cabfb3c8","75363fb3-42d1-49b3-a5f2-6bfdfe8186f7","39f5fc8b-c9e3-46b8-b73a-f2e293cd0ce7","c9a5dcc9-0dbb-46c0-81eb-228e08235345","8db98431-8234-49e2-a380-d6db57d3f86f","dec78d6b-790f-43a5-94f4-616cebd10345","521e6c4d-b5ac-48c7-ab12-2cdfd7e7032f"],"benchmarkVersion":"4-data-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Citation shareCitation share · observed Sep 20, 2026, 12:00 AM UTC2.941 percent100% confidence
Source
Rank.ai Data Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Engine breadthEngine breadth · observed Sep 20, 2026, 12:00 AM UTC1 engines100% confidence
Source
Rank.ai Data Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"data-platforms-2026-07-27","runArtifactIds":["360885b6-888c-4b84-b234-d98f3fbb248d","c72e77cb-1a63-447c-8ddb-8a30e3ebeb15","29e083f8-ff77-403d-9fd6-dcb93a67968b","5967da8a-0bb3-4c6f-ac82-cfabf774acc3","1686db53-6be4-4b90-9eb2-3f7df9f68389","3ab75670-79be-492c-8c80-f821ab00da2e","f898d076-6a23-4b06-a14d-de866de2c86d","8e361cdf-daa2-49f0-b643-4a410e8d9ae8","4e012623-ba28-4686-9f7a-34e82b1ea929","0fc840b7-d1d9-4960-a465-9562aaef8e2b","d1e24599-d01f-4cf1-9263-cd5515f38ab5","03f9920c-2ce4-4d67-81d9-05c625ff1862","d4751102-3faa-4eb3-8e1b-47e89eaa9862","20988919-d331-4cb0-aa13-d89105ae8016","d217cf56-b58d-4e4b-abac-50b32e68745f","cad206cd-350f-47d4-b557-57e66c7d5a31","2876054a-d15d-4059-a32c-6ae11c717ae2","19dfa956-fb61-4d80-a20c-1fe42303e16c","692ec6b6-0fd2-4b69-84a5-38cd27799136","7de9d72b-4ee1-404b-870c-063835484001","d02e5cd9-2619-4dc3-9c2a-72770f8e085f","49e1169c-302e-4ba4-bd55-41d52ba81405","9250031e-c201-4d08-97df-6574d8aadc0a","ea86f3b0-b5e5-47cd-9ce2-bddc28493fbc","78b36eae-87c4-4e87-a962-eafe0857dee8","41f14ffa-0bac-41b4-9607-44faa10247f0","5f7cd97b-9ac4-4cee-be99-6f1de1b79cec","2276f5fb-99ae-4ced-b55d-49e19fc85bff","3051fdf0-02e7-45ce-bb05-669043d3f24e","c29edf74-1c49-40c8-883d-2bb5cabfb3c8","75363fb3-42d1-49b3-a5f2-6bfdfe8186f7","39f5fc8b-c9e3-46b8-b73a-f2e293cd0ce7","c9a5dcc9-0dbb-46c0-81eb-228e08235345","8db98431-8234-49e2-a380-d6db57d3f86f","dec78d6b-790f-43a5-94f4-616cebd10345","521e6c4d-b5ac-48c7-ab12-2cdfd7e7032f"],"benchmarkVersion":"4-data-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Mention coverageMention coverage · observed Sep 20, 2026, 12:00 AM UTC2.778 percent100% confidence
Source
Rank.ai Data Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Reviewed-brand presence shareMention share · observed Sep 20, 2026, 12:00 AM UTC1.587 percent100% confidence
Source
Rank.ai Data Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Recommendation-prompt presenceRecommendation presence · observed Sep 20, 2026, 12:00 AM UTC4.167 percent100% confidence
Source
Rank.ai Data Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Gemini citation shareGemini brand citation share · observed Sep 20, 2026, 12:00 AM UTC5.263 percent100% confidence
Source
Rank.ai Data Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"data-platforms-2026-07-27","runArtifactIds":["360885b6-888c-4b84-b234-d98f3fbb248d","c72e77cb-1a63-447c-8ddb-8a30e3ebeb15","29e083f8-ff77-403d-9fd6-dcb93a67968b","5967da8a-0bb3-4c6f-ac82-cfabf774acc3","1686db53-6be4-4b90-9eb2-3f7df9f68389","3ab75670-79be-492c-8c80-f821ab00da2e","f898d076-6a23-4b06-a14d-de866de2c86d","8e361cdf-daa2-49f0-b643-4a410e8d9ae8","4e012623-ba28-4686-9f7a-34e82b1ea929","0fc840b7-d1d9-4960-a465-9562aaef8e2b","d1e24599-d01f-4cf1-9263-cd5515f38ab5","03f9920c-2ce4-4d67-81d9-05c625ff1862","d4751102-3faa-4eb3-8e1b-47e89eaa9862","20988919-d331-4cb0-aa13-d89105ae8016","d217cf56-b58d-4e4b-abac-50b32e68745f","cad206cd-350f-47d4-b557-57e66c7d5a31","2876054a-d15d-4059-a32c-6ae11c717ae2","19dfa956-fb61-4d80-a20c-1fe42303e16c","692ec6b6-0fd2-4b69-84a5-38cd27799136","7de9d72b-4ee1-404b-870c-063835484001","d02e5cd9-2619-4dc3-9c2a-72770f8e085f","49e1169c-302e-4ba4-bd55-41d52ba81405","9250031e-c201-4d08-97df-6574d8aadc0a","ea86f3b0-b5e5-47cd-9ce2-bddc28493fbc","78b36eae-87c4-4e87-a962-eafe0857dee8","41f14ffa-0bac-41b4-9607-44faa10247f0","5f7cd97b-9ac4-4cee-be99-6f1de1b79cec","2276f5fb-99ae-4ced-b55d-49e19fc85bff","3051fdf0-02e7-45ce-bb05-669043d3f24e","c29edf74-1c49-40c8-883d-2bb5cabfb3c8","75363fb3-42d1-49b3-a5f2-6bfdfe8186f7","39f5fc8b-c9e3-46b8-b73a-f2e293cd0ce7","c9a5dcc9-0dbb-46c0-81eb-228e08235345","8db98431-8234-49e2-a380-d6db57d3f86f","dec78d6b-790f-43a5-94f4-616cebd10345","521e6c4d-b5ac-48c7-ab12-2cdfd7e7032f"],"benchmarkVersion":"4-data-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Gemini mention coverageGemini brand mention coverage · observed Sep 20, 2026, 12:00 AM UTC8.333 percent100% confidence
Source
Rank.ai Data Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"data-platforms-2026-07-27","runArtifactIds":["360885b6-888c-4b84-b234-d98f3fbb248d","c72e77cb-1a63-447c-8ddb-8a30e3ebeb15","29e083f8-ff77-403d-9fd6-dcb93a67968b","5967da8a-0bb3-4c6f-ac82-cfabf774acc3","1686db53-6be4-4b90-9eb2-3f7df9f68389","3ab75670-79be-492c-8c80-f821ab00da2e","f898d076-6a23-4b06-a14d-de866de2c86d","8e361cdf-daa2-49f0-b643-4a410e8d9ae8","4e012623-ba28-4686-9f7a-34e82b1ea929","0fc840b7-d1d9-4960-a465-9562aaef8e2b","d1e24599-d01f-4cf1-9263-cd5515f38ab5","03f9920c-2ce4-4d67-81d9-05c625ff1862","d4751102-3faa-4eb3-8e1b-47e89eaa9862","20988919-d331-4cb0-aa13-d89105ae8016","d217cf56-b58d-4e4b-abac-50b32e68745f","cad206cd-350f-47d4-b557-57e66c7d5a31","2876054a-d15d-4059-a32c-6ae11c717ae2","19dfa956-fb61-4d80-a20c-1fe42303e16c","692ec6b6-0fd2-4b69-84a5-38cd27799136","7de9d72b-4ee1-404b-870c-063835484001","d02e5cd9-2619-4dc3-9c2a-72770f8e085f","49e1169c-302e-4ba4-bd55-41d52ba81405","9250031e-c201-4d08-97df-6574d8aadc0a","ea86f3b0-b5e5-47cd-9ce2-bddc28493fbc","78b36eae-87c4-4e87-a962-eafe0857dee8","41f14ffa-0bac-41b4-9607-44faa10247f0","5f7cd97b-9ac4-4cee-be99-6f1de1b79cec","2276f5fb-99ae-4ced-b55d-49e19fc85bff","3051fdf0-02e7-45ce-bb05-669043d3f24e","c29edf74-1c49-40c8-883d-2bb5cabfb3c8","75363fb3-42d1-49b3-a5f2-6bfdfe8186f7","39f5fc8b-c9e3-46b8-b73a-f2e293cd0ce7","c9a5dcc9-0dbb-46c0-81eb-228e08235345","8db98431-8234-49e2-a380-d6db57d3f86f","dec78d6b-790f-43a5-94f4-616cebd10345","521e6c4d-b5ac-48c7-ab12-2cdfd7e7032f"],"benchmarkVersion":"4-data-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Gemini recommendation-prompt presenceGemini brand recommendation presence · observed Sep 20, 2026, 12:00 AM UTC12.5 percent100% confidence
Source
Rank.ai Data Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
OpenAI citation shareOpenAI brand citation share · observed Sep 20, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Data Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"data-platforms-2026-07-27","runArtifactIds":["360885b6-888c-4b84-b234-d98f3fbb248d","c72e77cb-1a63-447c-8ddb-8a30e3ebeb15","29e083f8-ff77-403d-9fd6-dcb93a67968b","5967da8a-0bb3-4c6f-ac82-cfabf774acc3","1686db53-6be4-4b90-9eb2-3f7df9f68389","3ab75670-79be-492c-8c80-f821ab00da2e","f898d076-6a23-4b06-a14d-de866de2c86d","8e361cdf-daa2-49f0-b643-4a410e8d9ae8","4e012623-ba28-4686-9f7a-34e82b1ea929","0fc840b7-d1d9-4960-a465-9562aaef8e2b","d1e24599-d01f-4cf1-9263-cd5515f38ab5","03f9920c-2ce4-4d67-81d9-05c625ff1862","d4751102-3faa-4eb3-8e1b-47e89eaa9862","20988919-d331-4cb0-aa13-d89105ae8016","d217cf56-b58d-4e4b-abac-50b32e68745f","cad206cd-350f-47d4-b557-57e66c7d5a31","2876054a-d15d-4059-a32c-6ae11c717ae2","19dfa956-fb61-4d80-a20c-1fe42303e16c","692ec6b6-0fd2-4b69-84a5-38cd27799136","7de9d72b-4ee1-404b-870c-063835484001","d02e5cd9-2619-4dc3-9c2a-72770f8e085f","49e1169c-302e-4ba4-bd55-41d52ba81405","9250031e-c201-4d08-97df-6574d8aadc0a","ea86f3b0-b5e5-47cd-9ce2-bddc28493fbc","78b36eae-87c4-4e87-a962-eafe0857dee8","41f14ffa-0bac-41b4-9607-44faa10247f0","5f7cd97b-9ac4-4cee-be99-6f1de1b79cec","2276f5fb-99ae-4ced-b55d-49e19fc85bff","3051fdf0-02e7-45ce-bb05-669043d3f24e","c29edf74-1c49-40c8-883d-2bb5cabfb3c8","75363fb3-42d1-49b3-a5f2-6bfdfe8186f7","39f5fc8b-c9e3-46b8-b73a-f2e293cd0ce7","c9a5dcc9-0dbb-46c0-81eb-228e08235345","8db98431-8234-49e2-a380-d6db57d3f86f","dec78d6b-790f-43a5-94f4-616cebd10345","521e6c4d-b5ac-48c7-ab12-2cdfd7e7032f"],"benchmarkVersion":"4-data-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
OpenAI mention coverageOpenAI brand mention coverage · observed Sep 20, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Data Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
OpenAI recommendation-prompt presenceOpenAI brand recommendation presence · observed Sep 20, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Data Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source

Embed this table

Paste this on your site. It shows the latest published snapshot, and the credit line links readers to the full ranking.

<iframe src="https://www.rank.ai/embed/boards/data-platforms-brand-visibility" title="Data platforms brand visibility" width="100%" height="420" loading="lazy" style="border:1px solid #111;max-width:720px"></iframe>
<p style="font-size:12px">Source: <a href="https://www.rank.ai/rankings/data-platforms/data-platforms-brand-visibility">Data platforms brand visibility</a> by Rank.ai</p>

More in Data platforms

Cloud warehouses, lakehouses, streaming systems, and operational data platforms ranked across a fixed enterprise buying corpus.

3 boards

Data platform rank

Reviewed data platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

1Databricks133.3%
2MotherDuck429.2%
3Amazon Redshift229.2%

Data platform citation share

Reviewed vendors ranked by their share of the citations that point to vendor websites.

1Databricks217.6%
2MotherDuck14.7%
3Dremio214.7%

Data platform engine breadth

Reviewed vendors ranked by how many of the three model APIs name or cite them.

1MotherDuck63 engines
2Google BigQuery23 engines
3Snowflake23 engines

Data platform rank

Reviewed data platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Data platform citation share

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Data platform engine breadth

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.

Data platforms brand visibility

All 16 companies by mention coverage

One brand against up to three competitors, answer by answer

Which compared brands each answer names

The sites these answers cite

One brand against up to three competitors, answer by answer

Which compared brands each answer names

The sites these answers cite

Cloudera on Data Platforms Brand Visibility

What the score is built from

Unchanged since the previous snapshot

Where each number comes from

More in Data platforms

See how often AI names you.

One brand against up to three competitors, answer by answer

Which compared brands each answer names

The sites these answers cite