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Cube

One Semantic Foundation. Infinite Intelligence. Modernize how your organization delivers, consumes, and automates data and analytics.

Quick Info

Starting at $0.15 per Cube Consumption Unit
0 reviews
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Overview

Cube is a universal semantic layer designed to standardize and streamline how organizations manage and access their data. It acts as a central hub where data definitions, metrics, and access policies are defined once and then consistently applied across all data consumption tools, including BI platforms, custom applications, and AI agents. This approach eliminates data fragmentation and ensures that everyone in the organization is working with the same, trusted information. The platform's core value proposition lies in its ability to provide a consistent, governed, and optimized data experience. By offering robust data modeling capabilities, Cube allows users to define complex business metrics and relationships in a single place. Its powerful caching and pre-aggregation engine significantly accelerates query performance, making analytics faster and more cost-efficient. Furthermore, Cube's comprehensive API suite (AI, GraphQL, MDX, REST, SQL) ensures seamless integration with virtually any front-end application or data consumer, empowering organizations to deliver intelligent insights at scale.

Pricing

Starter

$0.15 per Cube Consumption Unit

  • Fully-hosted AWS / GCP
  • Development toolset
  • Semantic Layer Sync
  • Observability & high-availability
  • Extended query limit
  • Community Slack
  • Chat & Email
  • 2 support tickets per month
POPULAR

Premium

$0.30 per Cube Consumption Unit /per month

  • Everything in Starter
  • 99.950% Uptime SLA
  • Custom Domains
  • Unlimited queries
  • Multi-cluster Deployment
  • Performance Insights
  • On-Demand: Community Slack, Chat & Email, 4 support tickets per month
  • Commit: Unlimited support, Access to professional services, Volume discounts

Pros & Cons

Pros

  • Creates a single source of truth for metrics, reducing data inconsistencies.
  • Enhances data governance with centralized, fine-grained access control.
  • Significantly improves query performance and reduces costs through advanced caching.
  • Offers a wide range of APIs for flexible integration with front-end applications and AI tools.
  • Supports modern data stacks and cloud environments.
  • Open-source core with a strong community (18k+ GitHub stars, 12k+ Slack members).

Cons

  • Requires technical expertise to set up and manage the semantic layer effectively.
  • Can introduce an additional layer of complexity to the data stack.
  • Initial configuration and data modeling might be time-consuming for large datasets.
  • Reliance on Cube for all data definitions could create a single point of failure if not managed well.

Use Cases

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Best For

  • Building consistent dashboards and reports across multiple BI tools.
  • Powering customer-facing analytics in SaaS applications.
  • Providing governed data access for data scientists and AI agents.
  • Optimizing data query performance for large-scale analytical applications.
  • Creating a unified data view for cross-functional teams.
  • Enabling real-time analytics with pre-aggregated data.

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