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Cube

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

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Star Rating

22
4
0
0
1

Cube Reviews

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Profile Name
Star Rating
22
4
0
0
1
Steven L.
SL
Steven L.
06/25/2023
Validated Reviewer
Verified Current User
Review source: Seller invite
Incentivized Review

CubeJS Supercharges your analytics

|Cube
I have been using Cube for the better part of the last 2.5 years. It gave us an out-of-the-box abstraction to quickly slice and dice our data arbitrarily and provide insights and analytics layers for our customers. As Cube has grown, they have added more robust query result caching and pre-aggregation generation. We were fortunate enough that this lined up perfectly with our growth. As we collected more and more data, we knew Cube had our back in ensuring that we could continue to provide performant analytics to our customers.
Verified User in Hospital & Health Care
IH
Verified User in Hospital & Health Care
06/19/2023
Validated Reviewer
Verified Current User
Review source: Seller invite
Incentivized Review

Fast delivery and easy to use

|Cube
Cube helps us to quickly delivery features
Cirdes H.
CH
Cirdes H.
05/18/2023
Validated Reviewer
Verified Current User
Review source: Seller invite
Incentivized Review

Best embedded analytics tool

|Cube
Before Cube i was using iframes to embed data in my application. With cube it is easy to embed data with the look and feel of my application

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