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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
Raghuveer S.
RS
Raghuveer S.
07/06/2023
Validated Reviewer
Review source: Seller invite
Incentivized Review

Middle layer that provides cache, fast aggregations and a queryable data model abstraction

|Cube
Two Cube features that were particularly useful was that Cube is queryable with mutliple APIs : REST, GraphQL and SQL. This saved an enormous amount of time from building out this layer and allowed existing apps to query the Cube layer easily for relevant data. The other one was that the Cube store acts as a caching layer that not only caches queries but also provides very fast aggregations for analytical purposes. This helped create applications which could satisfy a broad range of requirements which made it applicable for both internal and external facing use cases.
Ariel S.
AS
Ariel S.
07/03/2023
Validated Reviewer
Verified Current User
Review source: Seller invite
Incentivized Review

App Developer Synergywfm.com

|Cube
Cube has made it much easier for us to generate information cubes and display them in our app that we are developing. It is very easy to use and has an intuitive playground that helps us build the queries and understand how it would work.
Verified User in Retail
CR
Verified User in Retail
06/28/2023
Validated Reviewer
Verified Current User
Review source: Seller invite
Incentivized Review

Ambitious BI product

|Cube
Very quick to prototype and visualise data, ambious set of supported databases and BI apps to connect with

About

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HQ Location:
San Francisco, CA

Social

@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