# How do companies store and query business data at scale without a dedicated tool?

Category: Data Warehouse. Intent: informational. Top brand: PostgreSQL.

Page: https://slateindex.ai/prompt/how-do-companies-store-and-query-business-data-at-scale-5ilzykcmre · data of 2026-11-03

## Brands named

| Brand | Share of engines |
|---|---|
| PostgreSQL | 100% |
| DuckDB | 100% |
| Trino | 100% |
| Snowflake | 67% |
| dbt | 67% |
| BigQuery | 67% |
| MySQL | 67% |
| Metabase | 67% |
| Apache Spark | 67% |
| Oracle Autonomous Data Warehouse | 33% |
| Teradata | 33% |
| Airbyte | 33% |
| Microsoft Azure | 33% |
| Fivetran | 33% |
| AWS | 33% |
| MotherDuck | 33% |

## Sources

- stripe.com (3)
- apache.org (2)
- google.com (2)
- trino.io (2)
- amazon.com (1)
- atlassian.com (1)
- cloudflare.com (1)
- fivetran.com (1)
- github.com (1)
- ibm.com (1)
- microsoft.com (1)
- motherduck.com (1)

## Definitions

- Visibility (0–100): how often and how high AI answers name the brand, weighted by position.
- Mention rate: share of collected AI answers that name the brand.
- Share of voice: the brand's mentions as a share of all brand mentions in the category.
- Citation authority: share of answers naming the brand that cite the brand's own site.

Cite as: SlateIndex, “How do companies store and query business data at scale without a dedicated tool?”, https://slateindex.ai/prompt/how-do-companies-store-and-query-business-data-at-scale-5ilzykcmre, data of 2026-11-03. Licence: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).