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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
Alejo B.
AB
Alejo B.
02/03/2026
Validated Reviewer
Review source: Organic

Powerful Semantic Layer, Poor Cloud Support

|Cube
I find Cube to be a very sophisticated product that allows me to design complex metrics and dimensions in a scalable and composable way. I also appreciate the useful caching (preaggregation) layer. Having a strong common semantic layer is key for us as a data product company serving dashboards and insights to our customers.
Verified User in Real Estate
UR
Verified User in Real Estate
09/18/2025
Validated Reviewer
Verified Current User
Review source: Organic

Super Easy Access to the DEV team

|Cube
Cube is a platform that presents the data in a very clear way. When we do the selection of column, it can also automatically generate sql code for SSMS. The query history is also great for tracking the error. When there's any problem, cube dev team is super easy to access, and they respond very fast. They really provide a strong tech support.
Verified User in Commercial Real Estate
UC
Verified User in Commercial Real Estate
01/21/2025
Validated Reviewer
Verified Current User
Review source: Seller invite
Incentivized Review

Great for AI applications and general data apps!

|Cube
I'm using CubeJS for a lot of data apps on my company and it is really incredible for leveraging data for my applications. I also use CubeJS daily for manual analytics, like taking a look at the charts or copying some data to perform some stronger statistical analysis. The interface simplicity of consumption for REST APIs is really powerful for integrating in any language and maintaining a standardized consumption around the tech ecosystem. This can also be used as a "Feature Store" of some sorts, together with the preAggregations layer, for ML and AI applications, making it really really simple to roll them out. I've already used the Customer Support and their response was really fast and the person helping me was also really proactive. The ability to test changes to a cube or creating a cube via Git branches is **really powerful**! It really helps! Finally, implementing cubes, measures, and also configuring dimensions is way too simple: we use it to connect to BigQuery and maintaining the semantics of metrics on CubeJS, which makes it so easy to understand data.

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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