Semantic & metrics layers · AtScale, Inc.

AtScale

Universal semantic layer that models metrics once on top of a cloud data warehouse and exposes them to any BI tool without data movement.

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AtScale is a warehouse-native semantic layer aimed at enterprises running multiple BI tools against the same cloud data warehouse. Analysts define dimensions, hierarchies, and calculated metrics once in AtScale's modeling layer, and those definitions are exposed as virtual cubes queryable through SQL, MDX, or REST from Tableau, Power BI, Excel, and other clients, without duplicating or exporting data out of the warehouse. AtScale focuses heavily on query acceleration, automatically building and managing aggregate tables so that BI tools get fast responses on large warehouse tables. It supports Snowflake, Databricks, BigQuery, and Redshift, and received a strategic investment from Snowflake in 2025–2026 as part of a broader push toward open, warehouse-native semantic layers. Pricing is consumption-based on the number of governed metrics and dimensions deployed, rather than per seat or per query.

At a glance

Vendor AtScale, Inc.
Pricing model Quote only
Free tier No
Deployment Cloud, Self-hosted
Open source No
Best for Enterprises running several BI tools against one warehouse who need one governed set of metrics and faster query performance.

Pricing

AtScale prices by 'Deployed Semantic Objects' (governed metrics and dimensions) rather than seats or queries; no dollar figures are published.

Checked on the vendor's own page on September 21, 2026: no prices are published. Expect to be quoted.

Features

  • Warehouse-native semantic modeling (no data movement)
  • Virtual cubes queryable via SQL, MDX, or REST
  • Automatic aggregate-table management for query acceleration
  • Consumption pricing based on deployed metrics, not seats
  • Compatible with Tableau, Power BI, Excel, and custom apps
  • Multi-cloud warehouse support (Snowflake, Databricks, BigQuery, Redshift)
  • Centralized governance for metric definitions

Integrations

Profile last reviewed September 21, 2026

Head to head

Alternatives

Cube Open-source headless semantic layer that defines metrics once and serves them via SQL, REST, and GraphQL APIs to any BI tool or app. Malloy Open-source modeling and query language that compiles to SQL, letting analysts define reusable metrics and explore data without repeating joins. dbt Transforms data already in the warehouse with SQL SELECT statements, adding version control, testing, documentation and lineage.

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Terms to know

Semantic layer A layer that defines business metrics and dimensions once, centrally, so every tool and report uses the same numbers. OLAP (online analytical processing) A category of technology optimized for fast, multi-dimensional aggregation and slicing of data for analysis. Business intelligence (BI) The practice of turning company data into dashboards, reports and metrics that guide business decisions. Data modeling The practice of organizing data into entities, relationships and schemas that make it accurate and efficient to query. Data warehouse A centralized, structured database optimized for fast historical reporting rather than day-to-day transactions.

Related guides

How to choose a semantic layer Semantic layers differ by where they sit relative to the warehouse and who they serve — one BI tool, every BI tool, an app, or an AI agent.