Cube Analytics
Analytics platforms
AI for data analytics tools
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
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$40 per developer per month
Free Trial unavailable
Free version
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- Accommodation and food services
- Information technology and software
- Real estate and property management
What is Cube Analytics
Cube Analytics is a business analytics platform used to model, query, and deliver metrics for reporting and embedded analytics use cases. It is typically used by data teams and product teams that need a semantic layer to standardize definitions (for example, revenue, retention, and funnel metrics) across BI tools and applications. The product focuses on defining reusable data models and serving consistent query results via APIs rather than being only a standalone dashboarding tool. It is often deployed alongside a cloud data warehouse and existing visualization or application front ends.
Semantic layer for metrics
Cube Analytics centers on a semantic layer that defines measures, dimensions, and business logic in one place. This helps reduce metric drift across dashboards and embedded analytics experiences. It supports reuse of definitions across multiple consuming tools and applications. This approach aligns with teams that want governed metrics without forcing a single visualization interface.
API-first analytics delivery
The platform is designed to serve analytics to multiple clients through APIs, which supports embedded analytics and custom applications. This can simplify integration patterns compared with tools that primarily assume interactive dashboards as the main output. It also enables programmatic access for internal services and data products. For engineering-led organizations, this can fit better into existing software delivery workflows.
Works with modern warehouses
Cube Analytics is commonly used with cloud data warehouses and lakehouse-style storage, allowing teams to keep data in their existing platforms. It can sit between the warehouse and downstream tools to manage query patterns and metric definitions. This can reduce duplicated transformation logic across BI projects. It also supports incremental adoption without replacing the underlying data store.
Requires data modeling effort
Teams typically need to design and maintain a semantic model, which adds upfront work compared with purely self-service BI experiences. Ongoing changes to business logic require versioning and governance processes. Organizations without dedicated analytics engineering resources may find adoption slower. The benefits depend on consistent model maintenance over time.
Not a full BI suite
Cube Analytics is not primarily a complete end-to-end BI environment with native dashboard authoring as the core workflow. Many deployments still rely on separate visualization tools or custom front ends for reporting. This can increase the number of components to manage. Buyers expecting an all-in-one analytics UI may need additional products.
AI features may vary
AI-assisted analytics capabilities (such as natural-language querying, automated insights, or narrative explanations) depend on the specific edition, integrations, and configuration. Some AI workflows may require pairing with external tools or additional services. Governance and accuracy controls for AI-generated outputs can require extra setup. Organizations should validate AI functionality against their exact use cases before standardizing.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Free | $0 — Free forever | Connect any data source; model in semantic layer IDE; explore workbooks; publish dashboards; includes two development instances; 1,000 query/day limit (per docs). |
| Starter | $40 per Developer / month | Everything in Free, plus extended agent limits; premium LLMs; unlimited workbooks; extended query limits; production deployment compute (hourly fees may apply); Cube Store caching; Semantic Layer Sync; observability & high-availability. (Seat-based price shown on cube.dev/pricing). |
| Premium | $80 per Developer / month | Everything in Starter, plus Explorer role; embedded dashboards & analytics chat; unlimited queries; 99.950% uptime SLA; custom domains; multi-cluster deployment; performance insights. |
| Enterprise | Custom pricing | Everything in Premium, plus 99.990% SLA; dedicated single-tenant installation; Bring Your Own Cloud (BYOC) & Bring Your Own LLM (BYOLLM); SSO with SAML 2.0; workspace access control; DAX API for Power BI; dedicated infrastructure (VPC) starts at $12,000. |
Additional usage/compute pricing published on Cube’s official pages (usage-based/CCU model):
- CCU (Cube Compute Unit) pricing (learn.cube.dev): Starter $0.10 per CCU (minimum commit: $99/mo); Premium $0.25 per CCU (minimum commit: $10,000/year); Enterprise $0.40 per CCU (minimum commit: $20,000/year).
- Production deployment compute (as shown on cube.dev/pricing compare table): Starter $0.60 / hour; Premium $1.20 / hour; Enterprise: custom.
- Cube Store caching (small): Starter $0.15 / hour / worker; Premium $0.30 / hour / worker.
- Additional API instances: Starter $0.15 / hour / instance; Premium $0.30 / hour / worker.
Notes: Cube’s official site presents both seat-based tier pricing (per-developer monthly rates) and a CCU-based usage pricing model with minimum commits on different pages. Do not mix or extrapolate beyond what is published on the vendor site.
Seller details
Cube Dev, Inc.
San Francisco, California, United States
2019
Private
https://cube.dev/
https://x.com/the_cube_dev
https://www.linkedin.com/company/cube-dev
