Data platform rank

As of

All 16 companies by recommendation prompt presence

Databricks leads at 33.3%; the middle of the board sits at 10.4%.

Ahead of second place: 4.2%
Held by the top three: 45%
Middle of the board: 10.4%
Below half the leader: 11 of 16

Rank, name and recommendation prompt presenceMiddle 10.4%

1Databricks33.3%
2MotherDuck29.2%
3Amazon Redshift29.2%
4Google BigQuery25.0%
5Snowflake20.8%
6Dremio12.5%
7Confluent12.5%
8ClickHouse Cloud12.5%
9Microsoft Fabric8.3%
10Teradata VantageCloud8.3%
11Cloudera4.2%
12Firebolt4.2%
13SingleStore4.2%
14Oracle Autonomous Database0.0%
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.

24 checks behind each row · 100% confidence across rows.

Data platform rank current rankings
Rank	Name	Recommendation prompt presence	Mention coverage	Share of names	Cited as source	Change	Why
01	Databricks	33.3%	27.78% · 10 / 36	15.87% · 10 / 63	17.65% · 6 / 34	1	This rank My rank
02	MotherDuck	29.2%	22.22% · 8 / 36	12.7% · 8 / 63	14.71% · 5 / 34	4	This rank My rank
03	Amazon Redshift	29.2%	22.22% · 8 / 36	12.7% · 8 / 63	8.82% · 3 / 34	2	This rank My rank
04	Google BigQuery	25.0%	25% · 9 / 36	14.29% · 9 / 63	2.94% · 1 / 34	1	This rank My rank
05	Snowflake	20.8%	22.22% · 8 / 36	12.7% · 8 / 63	8.82% · 3 / 34	1	This rank My rank
06	Dremio	12.5%	13.89% · 5 / 36	7.94% · 5 / 63	14.71% · 5 / 34	5	Showing My rank
07	Confluent	12.5%	8.33% · 3 / 36	4.76% · 3 / 63	5.88% · 2 / 34		This rank My rank
08	ClickHouse Cloud	12.5%	8.33% · 3 / 36	4.76% · 3 / 63	2.94% · 1 / 34	7	This rank My rank
09	Microsoft Fabric	8.3%	8.33% · 3 / 36	4.76% · 3 / 63	5.88% · 2 / 34	5	This rank My rank
10	Teradata VantageCloud	8.3%	5.56% · 2 / 36	3.17% · 2 / 63	5.88% · 2 / 34	2	This rank My rank
11	Cloudera	4.2%	2.78% · 1 / 36	1.59% · 1 / 63	2.94% · 1 / 34		This rank My rank
12	Firebolt	4.2%	2.78% · 1 / 36	1.59% · 1 / 63	2.94% · 1 / 34	2	This rank My rank
13	SingleStore	4.2%	2.78% · 1 / 36	1.59% · 1 / 63	2.94% · 1 / 34		This rank My rank
14	Oracle Autonomous Database	0.0%	2.78% · 1 / 36	1.59% · 1 / 63	2.94% · 1 / 34	2	This rank My rank
15	MongoDB Atlas	0.0%	0% · 0 / 36	0% · 0 / 63	0% · 0 / 34	1	This rank My rank
16	Starburst	0.0%	0% · 0 / 36	0% · 0 / 63	0% · 0 / 34	7	This rank My rank

24 checks behind each row · 100% confidence across rows.

Data platform rank current rankings
Rank	Name	Recommendation prompt presence	Mention coverage	Share of names	Cited as source	Change	Why
01	Databricks	33.3%	27.78% · 10 / 36	15.87% · 10 / 63	17.65% · 6 / 34	1	This rank My rank
02	MotherDuck	29.2%	22.22% · 8 / 36	12.7% · 8 / 63	14.71% · 5 / 34	4	This rank My rank
03	Amazon Redshift	29.2%	22.22% · 8 / 36	12.7% · 8 / 63	8.82% · 3 / 34	2	This rank My rank
04	Google BigQuery	25.0%	25% · 9 / 36	14.29% · 9 / 63	2.94% · 1 / 34	1	This rank My rank
05	Snowflake	20.8%	22.22% · 8 / 36	12.7% · 8 / 63	8.82% · 3 / 34	1	This rank My rank
06	Dremio	12.5%	13.89% · 5 / 36	7.94% · 5 / 63	14.71% · 5 / 34	5	Showing My rank
07	Confluent	12.5%	8.33% · 3 / 36	4.76% · 3 / 63	5.88% · 2 / 34		This rank My rank
08	ClickHouse Cloud	12.5%	8.33% · 3 / 36	4.76% · 3 / 63	2.94% · 1 / 34	7	This rank My rank
09	Microsoft Fabric	8.3%	8.33% · 3 / 36	4.76% · 3 / 63	5.88% · 2 / 34	5	This rank My rank
10	Teradata VantageCloud	8.3%	5.56% · 2 / 36	3.17% · 2 / 63	5.88% · 2 / 34	2	This rank My rank
11	Cloudera	4.2%	2.78% · 1 / 36	1.59% · 1 / 63	2.94% · 1 / 34		This rank My rank
12	Firebolt	4.2%	2.78% · 1 / 36	1.59% · 1 / 63	2.94% · 1 / 34	2	This rank My rank
13	SingleStore	4.2%	2.78% · 1 / 36	1.59% · 1 / 63	2.94% · 1 / 34		This rank My rank
14	Oracle Autonomous Database	0.0%	2.78% · 1 / 36	1.59% · 1 / 63	2.94% · 1 / 34	2	This rank My rank
15	MongoDB Atlas	0.0%	0% · 0 / 36	0% · 0 / 63	0% · 0 / 34	1	This rank My rank
16	Starburst	0.0%	0% · 0 / 36	0% · 0 / 63	0% · 0 / 34	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.

6

Rank on this board

12.5 percent

Score

24

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 Dremio's score
Component	Value	Contribution
Recommendation presence	12.5	12.5

Moved down since the previous snapshot

-5 places

Gemini brand recommendation presence50 to 12.5
-37.5
Gemini brand mention coverage41.667 to 16.667
-25
Gemini brand citation share25 to 10.526
-14.474
Recommendation presence25 to 12.5
-12.5
Citation share25 to 14.706
-10.294
Mention share16.327 to 7.937
-8.39
Mention coverage22.222 to 13.889
-8.333
OpenAI brand citation share25 to 20
-5
Anthropic brand mention coverage0 to 0
0
Anthropic brand recommendation presence0 to 0
0
Engine breadth2 to 2
0
OpenAI brand mention coverage25 to 25
0
OpenAI brand recommendation presence25 to 25
0

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 UTC14.706 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 UTC2 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 UTC13.889 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 UTC7.937 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 UTC12.5 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 UTC10.526 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 UTC16.667 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 UTC20 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 UTC25 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 UTC25 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-platform-brand-rank" title="Data platform rank" 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-platform-brand-rank">Data platform rank</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 presence

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

1Databricks127.8%
2Google BigQuery125%
3MotherDuck222.2%

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 presence

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

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 platform rank

All 16 companies by recommendation prompt presence

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

Dremio on Data Platform Rank

What the score is built from

Moved down 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