Data as of Oct 18, 2026Based on 399 AI responses
Reviewed by Dimitry Apollonsky
AI summary
Looker holds a narrow lead over AtScale as a BI-native modeling layer tied closely to Google Cloud analytics. When teams need to manage data models as code or handle complex enterprise table joins, dbt is the usual answer.
Rank and Mentioned in · since Jul 5
| # | Brand | Recommended for | Mentioned in |
|---|---|---|---|
| 1 | proprietary LookML modeling for organizations committed to the Google Cloud stack | proprietary LookML modeling for organizations committed to the Google Cloud stack | 45% |
| 2 | centralized enterprise data virtualization, complex business logic, and cross-tool governance | centralized enterprise data virtualization, complex business logic, and cross-tool governance | 38% |
| 3 | YAML-defined metrics powered by MetricFlow alongside existing dbt data transformations | YAML-defined metrics powered by MetricFlow alongside existing dbt data transformations | 32% |
| 4 | version-controlled metrics and semantic modeling for analytics engineering workflows | version-controlled metrics and semantic modeling for analytics engineering workflows | 32% |
| 5 | lakehouse-native natural language querying and metric views via Unity Catalog | lakehouse-native natural language querying and metric views via Unity Catalog | 30% |
| 6 | warehouse-native semantic views and conversational queries using Cortex AI | warehouse-native semantic views and conversational queries using Cortex AI | 30% |
| 7 | code-based modeling of metrics and dimensions directly inside Looker | code-based modeling of metrics and dimensions directly inside Looker | 27% |
| 8 | an open-source Python framework for training custom text-to-SQL generation | an open-source Python framework for training custom text-to-SQL generation | 27% |
| 9 | embedded BI semantic modeling and read-only natural language exploration | embedded BI semantic modeling and read-only natural language exploration | 25% |
| 10 | search-first enterprise self-service analytics that turns natural language into Liveboards | search-first enterprise self-service analytics that turns natural language into Liveboards | 24% |
| 11 | 22% | ||
| 12 | 22% | ||
| 13 | 19% | ||
| 14 | 18% | ||
| 15 | 17% |
What’s changing · since July
Since July, Databricksrising and Snowflakerising have become common answers for natural language BI interfaces, while Wrenrising has entered regular rotation. Meanwhile, AI2sqlfalling is now named only occasionally for natural language business data search.
Weeks of Aug 17 – Oct 4, 2026 · Since Jul 5
Widest split: Vanna, 19% on ChatGPT Search and 35% on Google AI Mode.
| Brand | ChatGPT Search | Google AI Mode | Comparison |
|---|---|---|---|
| Looker | 50% | 39% | |
| AtScale | 45% | 32% | |
| dbt Semantic Layer | 32% | 32% | |
| dbt | 32% | 32% | |
| Databricks | 31% | 29% | |
| Snowflake | 29% | 30% | |
| LookML | 34% | 21% | |
| Vanna | 19% | 35% | |
| Microsoft Power BI | 32% | 17% | |
| ThoughtSpot | 27% | 21% |
58% of citations point at the ranked brands’ own sites. youtube.com, reddit.com, medium.com are the most-cited sites outside the ranked brands’ own domains.
Market map
Mentioned in · since Jul 5
Leading brands by topic
I'm looking for an AI assistant that can take plain English questions and turn them into optimized SQL queries, specifically for handling complex joins.
I need a way for non-technical employees to pull data from our database without knowing SQL. Are there any platforms that support plain English database queries?
I'm looking to provide a "natural language" interface to our business data. What is the best Text-to-SQL or semantic search platform for BI?
I need to build a semantic layer for our BI tools. What's the best software for that?
We use an SQL database. Who offers a natural language interface that adheres to read-only permissions?
Our text-to-SQL generation fails on complex table joins. Who specializes in semantic layers for enterprise databases?
What is the best tool for creating and managing a semantic layer for our business intelligence tools?
My goal is to manage our data models as code. What's the best semantic layer or metrics store for a growing data team?