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Cube

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27 reviews
  • 1 profiles
  • 3 categories
Average star rating
4.5
Serving customers since
2019

Profile Name

Star Rating

22
4
0
0
1

Cube Reviews

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Profile Name
Star Rating
22
4
0
0
1
David  R.
DR
David R.
03/06/2023
Validated Reviewer
Verified Current User
Review source: Organic

A modern and flexible semantic layer for building cloud based applications at scale.

|Cube
The best part about Cube is how easily we can define and standardize our application's data layer and reporting capabilities. We've ensured consistent calculations of measures across consumers, enforced custom data security rules and, most importantly, scaled our application without friction.
Alessandro L.
AL
Alessandro L.
03/06/2023
Validated Reviewer
Verified Current User
Review source: Organic

Cube.dev: where data modeling done right and software engineering best practices meet together

|Cube
Cube.dev approach to data modeling is powerful and very flexible. Cube Cloud deployments make it easier to test your data models with a CI/CD approach.
Bruce S.
BS
Bruce S.
03/06/2023
Validated Reviewer
Verified Current User
Review source: Organic

Tons of functionality and super easy to use

|Cube
Cube has a ton of functionality -- from querying, serving and caching to static and dynamic schemas and complicated preaggregations from one or more data sources. Often when a tool nears this level of functionality it becomes hard to use, yet Cube maintains all of the attributes that make it simple to get started with and use.

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HQ Location:
San Francisco, CA

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@the_cube_dev

What is Cube?

Cube is the agentic analytics platform — built on a semantic layer. Cube is the AI-native generation of business intelligence. It's one platform for two use cases: internal BI, where data teams and business users analyze their own company's data, and embedded analytics, where software companies ship analytics inside their own products. The same governed semantic layer powers both. What makes AI answers trustworthy in production is the semantic layer underneath them. Cube was built around the semantic layer from day one rather than retrofitting one onto a dashboard- or notebook-first tool. The data team's governed metric definitions stay intact while AI constructs ad-hoc calculations on top of them — so you get governance and flexibility at the same time, not one at the expense of the other. That's why teams like Brex chose Cube to power AI-driven analytics at production scale. With Cube, data teams can: Model metrics and business definitions once, in a SQL-first semantic layer, and serve them consistently to every downstream consumer — AI agents, BI, spreadsheets, and embedded apps. Let business users ask questions in natural language through Analytics Chat, with answers grounded in the governed model instead of guessed from raw tables. Bring analytics to where people already work — Slack, and any MCP-compatible agent like Claude or ChatGPT via the Cube MCP server. Embed analytics in customer-facing products with multi-tenancy, row-level security, and query performance under load — choosing from a chat API, drop-in iframes, embedded creator mode, or data APIs. Apply software engineering best practices to analytics: version control with Git, CI/CD, isolated environments, and pre-aggregation caching for fast queries and lower warehouse spend. Cube Core, the open-source semantic layer at its foundation, has years of production use across a large developer community — battle-tested infrastructure that commercial-only tools can't match. Cube sits on top of your cloud data warehouse (Snowflake, BigQuery, Redshift, Databricks); it doesn't replace it.

Details

Year Founded
2019
Website
cube.dev