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Databricks AI/BI vs Cortex Analyst: what each is built for, and when neither fits

Databricks AI/BI vs Cortex Analyst compared: what each is built for, what it needs before the first answer, and a file-first option when neither fits.

The short answerBoth answer natural-language questions over data already in their platform. Genie is a finished interface that analysts curate; Cortex Analyst is an API developers build into applications, guided by semantic views. Databricks AI/BI suits organisations that already keep their data in Databricks and Unity Catalog; Cortex Analyst suits organisations whose data already lives in Snowflake and who want natural-language questions without moving it. When the need is one desk's question answered from the exports it already has, a file-first tool may fit better than either.

Databricks AI/BI and Cortex Analyst are both good at what they are built for. Both answer natural-language questions over data already in their platform. Genie is a finished interface that analysts curate; Cortex Analyst is an API developers build into applications, guided by semantic views. This guide sets them side by side, fairly, and ends with the case where a team needs neither.

At a glance

Databricks AI/BI Cortex Analyst Covirage
Built for Organisations that already keep their data in Databricks and Unity Catalog; Data teams that want to give business users self-service questions without adding a separate BI licence Organisations whose data already lives in Snowflake and who want natural-language questions without moving it; Development teams building a chat or question-answering feature into an internal or customer-facing app The person waiting for the answer, in a big or medium company
How it gets data Live query of data registered in Unity Catalog, run on a Databricks SQL warehouse (pro or serverless for Genie). Data outside Databricks first needs to be brought into or federated through the platform. Live query of tables in Snowflake. Cortex Analyst generates SQL against the tables described in a semantic view, and that SQL is executed on a Snowflake virtual warehouse. Data from other systems must first be loaded into or shared with Snowflake. Files and sheets now; scheduled delivery by API, S3, Azure, SFTP or email on Business; connections built with your team on Enterprise
Needs before the first answer A Databricks workspace with data registered in Unity Catalog; A pro or serverless SQL warehouse and the Databricks SQL entitlement; An analyst or data team to curate each Genie space with tables, instructions and example queries A Snowflake account with the relevant data loaded; Semantic views describing tables, metrics, synonyms, joins and verified queries; A developer to call the REST API from an application, or an agent configured in Cortex Agents or Snowflake CoWork The exports your systems already produce. No warehouse, no modelling language, no data team
AI Genie uses generative AI to turn a natural-language question into SQL, which runs on the chosen SQL warehouse under the user's own Unity Catalog permissions. Accuracy is shaped by Unity Catalog metadata, metric views and the instructions, sample SQL queries and benchmarks that authors add to a Genie space (up to 50 tables, views or metric views per space). Dashboards also include AI assistance for building datasets and visualisations. An LLM-powered service translates a natural-language question into SQL, guided by semantic views (descriptions, synonyms, join paths, metrics and verified example queries). The generated SQL runs in Snowflake and results are returned to the calling application. Since August 2026 Snowflake recommends invoking it through Cortex Agents, which uses the same semantic views for SQL generation; Snowflake CoWork (formerly Snowflake Intelligence) is the end-user agent built on this. The AI model chooses a measure and writes the explanation; our tools do the arithmetic and check every total
Published pricing There is no additional licence fee for AI/BI; standard Databricks DBU rates apply to the SQL warehouse compute that runs queries. For Genie's LLM usage, each user receives 150 DBUs free per month (quoted as $10.50 in US East, varying by region); usage beyond that is billed in DBUs, and warehouse compute is billed separately. Databricks offers a 14-day free trial. Consumption-based. Through the Cortex Analyst REST API, Snowflake's Service Consumption Table (effective 23 September 2026) lists 67 platform credits per 1,000 messages, with only successful responses counted; warehouse compute to run the generated SQL is billed separately. On-demand platform credits are listed at $2.00 (Standard), $3.00 (Enterprise) and $4.00 (Business Critical) in AWS US East (Northern Virginia). Use through Cortex Agents is billed on the token-based model for agents instead. Three tiers on one sheet, shared in a conversation

Databricks AI/BI in brief

AI/BI is the business intelligence layer built into the Databricks Data Intelligence Platform. It has two parts: Dashboards, a low-code tool for building and sharing interactive dashboards, and Genie, a conversational interface where business users ask questions in natural language. Both run directly on data governed in Unity Catalog.

  • Databricks was founded in 2013 by the creators of Apache Spark from UC Berkeley's AMPLab.
  • Databricks announced AI/BI, made up of Dashboards and Genie, on 12 June 2024, with Dashboards generally available and Genie in public preview.
  • At launch, Databricks said AI/BI carried no licence fee beyond warehouse compute costs for Databricks SQL Pro and Serverless customers.
  • Databricks announced general availability of AI/BI Genie on 12 June 2025.

Cortex Analyst in brief

Cortex Analyst is a fully managed Snowflake feature that answers business questions in natural language by generating SQL over structured data held in Snowflake. It is offered as a REST API that developers build into their own applications, and it relies on semantic views that describe the business meaning of tables. Snowflake's own conversational agent product, launched as Snowflake Intelligence and now called Snowflake CoWork, uses the same semantic views through Cortex Agents.

  • Snowflake was founded in 2012 by Benoît Dageville, Thierry Cruanes and Marcin Żukowski.
  • Snowflake reported revenue of $4.68 billion for fiscal year 2026.
  • Cortex Analyst was released in preview on 14 August 2024 as a way to answer business questions over structured data in Snowflake.
  • Cortex Analyst uses semantic views to understand data and generate SQL, and is offered as a REST API.

Where Databricks AI/BI fits best

  • Organisations that already keep their data in Databricks and Unity Catalog.
  • Data teams that want to give business users self-service questions without adding a separate BI licence.
  • Companies wanting dashboards, natural-language questions and data engineering governed in one place.

Where Cortex Analyst fits best

  • Organisations whose data already lives in Snowflake and who want natural-language questions without moving it.
  • Development teams building a chat or question-answering feature into an internal or customer-facing app.
  • Data teams prepared to maintain semantic views and verified queries as a governed layer for AI.

Where they differ

Data

Databricks AI/BI. Live query of data registered in Unity Catalog, run on a Databricks SQL warehouse (pro or serverless for Genie). Data outside Databricks first needs to be brought into or federated through the platform.

Cortex Analyst. Live query of tables in Snowflake. Cortex Analyst generates SQL against the tables described in a semantic view, and that SQL is executed on a Snowflake virtual warehouse. Data from other systems must first be loaded into or shared with Snowflake.

AI

Databricks AI/BI. Genie uses generative AI to turn a natural-language question into SQL, which runs on the chosen SQL warehouse under the user's own Unity Catalog permissions. Accuracy is shaped by Unity Catalog metadata, metric views and the instructions, sample SQL queries and benchmarks that authors add to a Genie space (up to 50 tables, views or metric views per space). Dashboards also include AI assistance for building datasets and visualisations.

Cortex Analyst. An LLM-powered service translates a natural-language question into SQL, guided by semantic views (descriptions, synonyms, join paths, metrics and verified example queries). The generated SQL runs in Snowflake and results are returned to the calling application. Since August 2026 Snowflake recommends invoking it through Cortex Agents, which uses the same semantic views for SQL generation; Snowflake CoWork (formerly Snowflake Intelligence) is the end-user agent built on this.

What each needs before the first answer

Databricks AI/BI:

  • A Databricks workspace with data registered in Unity Catalog.
  • A pro or serverless SQL warehouse and the Databricks SQL entitlement.
  • An analyst or data team to curate each Genie space with tables, instructions and example queries.

Cortex Analyst:

  • A Snowflake account with the relevant data loaded.
  • Semantic views describing tables, metrics, synonyms, joins and verified queries.
  • A developer to call the REST API from an application, or an agent configured in Cortex Agents or Snowflake CoWork.

When neither fits

Both assume a team that will build and maintain a model of the data before questions get answered. Some teams have a narrower need: one desk, one recurring question such as "what is driving my costs" or "where is my revenue coming from", and exports that already exist. For them, Covirage reads those files, answers the question with a bridge that sums to the change, and is set up for them within a week. The AI model chooses the measure and explains it; our tools do the arithmetic.

See the full pages on Databricks AI/BI alternatives and Cortex Analyst alternatives, or how to evaluate an analytics vendor.

Sources

Facts about other products were checked on 24 September 2026 from the pages below. Product names are trademarks of their owners; Covirage is not affiliated with them.

Questions people ask

What is the main difference between Databricks AI/BI and Cortex Analyst?

Both answer natural-language questions over data already in their platform. Genie is a finished interface that analysts curate; Cortex Analyst is an API developers build into applications, guided by semantic views.

Which is easier to start with, Databricks AI/BI or Cortex Analyst?

It depends on what is in place. For Databricks AI/BI: A Databricks workspace with data registered in Unity Catalog; A pro or serverless SQL warehouse and the Databricks SQL entitlement; An analyst or data team to curate each Genie space with tables, instructions and example queries. For Cortex Analyst: A Snowflake account with the relevant data loaded; Semantic views describing tables, metrics, synonyms, joins and verified queries; A developer to call the REST API from an application, or an agent configured in Cortex Agents or Snowflake CoWork. Check both against your team and your data before comparing licence prices.

Is there an alternative to both?

For a desk that needs to explain why its numbers moved, from exports it already produces, Covirage answers from the file and is set up for you within a week. It does not replace a platform for the whole organisation.