Pricing in Cube Cloud
Cube Cloud pricing is based on resource consumption which we measure using Cube Consumption Units in 5 minute intervals. Each product tier has different features and functionality that you should review as you think about what is right for your business.
Cube Consumption Unit
Cube Consumption Unit (CCU) is a way to measure resource consumption used to run Cube Cloud infrastructure and resources within it.
The price of a CCU is determined by the product tier you're subscribed to. Each product tier determines the features, scalability, availability, as well as the speed and scope of support you may receive for your deployment.
You can also set Budgets to make sure you know your usage is on track and as expected.
Payment plans
Payment plans determine whether you have a fixed-term contract or a recurring subscription:
- On-demand payment plan allows you to subscribe at any time, add your credit card, and start using Cube Cloud right away. Starter and Premium product tiers are available on the on-demand payment plan.
- Commit payment plan allows you to have a contract with a CCU amount specified in an order form. Premium, Enterprise, and Enterprise Premier product tiers are available on the commit payment plan. Contact us (opens in a new tab) to learn more.
Product tiers
Free
Free product tier is designed for development and testing purposes. It is not intended for production use.
It offers up to two Development Instances.
You can review its support terms and limits.
Starter
Starter product tier targets low-scale production that is not business-critical.
It offers a Production Cluster, the ability to use third-party packages from the npm registry, AWS and GCP support in select regions, pre-aggregations of up to 150GB in size, auto-suspend controls, and Semantic Layer Sync with a single BI tool (such as Preset or Metabase).
You can review its pricing (opens in a new tab), support terms, and limits.
Premium
Premium product tier is designed for basic small-scale production deployments.
It offers everything in the Starter product tier as well as enabling the use of Production Multi-Clusters, support for custom domains, AWS and GCP support in all regions. Cube Cloud provides a 99.95% uptime SLA for this product tier.
You can review its pricing (opens in a new tab), support terms, and limits.
Enterprise
Enterprise product tier is suitable for high-scale or mission-critical production deployments with more significant security and compliance needs.
It offers everything in the Premium product tier as well as Semantic Layer Sync with unlimited supported BI tools, SAML 2.0 support for single sign-on, Azure support for all regions, dedicated infrastructure, VPC peering, monitoring integrations, and role-based access control. Cube Cloud provides a 99.99% uptime SLA for this product tier.
You can review its pricing (opens in a new tab), support terms, and limits.
Enterprise Premier
Enterprise Premier product tier caters to high-scale, high-availability mission-critical production deployments with security and compliance needs.
It offers everything in the Enterprise product tier as well as unlimited pre-aggregation sizes, and support for kSQL and Elasticsearch. Cube Cloud provides a 99.995% uptime SLA for this product tier.
You can review its pricing (opens in a new tab), support terms, and limits.
Resources
The following resource types incur CCU consumption (measured in 5-minute intervals):
| Resource type | CCUs per hour |
|---|---|
| Production Cluster | Depends on a chosen tier |
| Development Instance | Depends on a chosen tier |
| Cube API Instance | Depends on a chosen tier |
| Cube Store Worker | Depends on a chosen tier |
| Semantic Catalog | Depends on a chosen tier |
| Dedicated infrastructure | 3 |
| Query History | Depends on a chosen tier |
| Monitoring Integrations | Depends on a chosen tier |
| Audit Log | Depends on a chosen tier |
Deployment tiers
Production clusters (including individual API instances) and development instances are involved in serving requests through APIs & integrations under the following tiers:
| Tier | Dependent features | ||
|---|---|---|---|
| S | 100% | — | |
| M | 200% |
You can upgrade to a chosen tier in the Settings of your deployment. Upgrading to the M tier is only available on Enterprise and above (opens in a new tab) product tiers.
Cube Store Worker tiers
Cube Store workers are involved in building pre-aggregations and executing queries against them under the following tiers:
| Tier | Throughput | Dependent features | |
|---|---|---|---|
| S | 1 | 100% | — |
| M | 2 | 200% | Data-at-rest encryption with customer-managed keys in Cube Store |
You can upgrade to a chosen tier in the Settings of your deployment.
Semantic Catalog tiers
Semantic Catalog provides observability into other data tools interoperating with your data model under the following tiers:
| Tier | Data assets | |
|---|---|---|
| S | 2 | Up to 30,000 |
| M | 4 | Up to 100,000 |
You can upgrade to a chosen tier in the Settings of your deployment.
Query History tiers
Query History and Performance Insights features analyze and visualize the data available under the following tiers:
| Tier | CCUs per hour | API requests | Data retention |
|---|---|---|---|
| XS | 0 | Up to 50,000/day | 1 day |
| S | 2 | Up to 100,000/day | 7 days |
| M | 5 | Up to 250,000/day | 14 days |
| L | 10 | Up to 500,000/day | 21 days |
| XL | 20 | Up to 1,000,000/day | 30 days |
You can upgrade to a chosen tier in the Settings of your deployment.
Monitoring Integrations tiers
Monitoring Integrations feature has the following tiers:
| Tier | CCUs per hour | Exported data |
|---|---|---|
| XS | 1 | Up to 10 GB/mo |
| S | 2 | Up to 25 GB/mo |
| M | 4 | Up to 50 GB/mo |
You can upgrade to a chosen tier in the Settings of your deployment.
Audit Log tiers
Audit Log collects, stores, and displays security-related events under the following tiers:
| Tier | Dependent features | |
|---|---|---|
| S | 4 | — |
| M | 6 | Audit Log data export |
Total cost examples
The following examples provide insight into the total cost to use Cube Cloud:
- Small-scale deployment (production cluster, Premium product tier).
- Medium-scale deployment (production cluster with auto-scaling, Enterprise product tier).
- Large-scale deployment (production multi-cluster with dedicated infrastructure, Enterprise product tier).
Small-scale deployment
Suppose a company uses Cube Cloud to power self-serve business intelligence for a couple of teams in Eastern and Pacific time zones.
This organization:
- Uses the Premium product tier of Cube Cloud.
- Runs a single Production Cluster that is active 24/7 but never has to auto-scale its API instances because the usage is spread evenly with no bursts.
- Operates on a small volume of data that requires the usage of just 2 Cube Store Workers to run queries and refresh pre-aggregations mostly during working hours, being active approximately 50% of the time.
- Updates its data model infrequently and without using a dedicated Development Instance for testing purposes, with 2 data engineers spending just 1 hour a day each, in the development mode of the Production Cluster.
| Resource | Usage per month | CCU per month |
|---|---|---|
| Production Cluster | 1 Production Cluster × 24 hours per day × 30 days | 720 hours × 4 CCUs per hour = 2880 CCUs |
| Additional Cube API Instance | — | — |
| Cube Store Worker | 2 Cube Store Workers × 12 hours per day × 30 days | 720 hours × 1 CCU per hour = 720 CCUs |
| Development Instance | — | — |
| Development Instance (for development mode) | 2 users × 1 hour per day × 30 days | 60 hours × 1 CCU per hour = 60 CCUs |
| Total | 3660 CCUs |
Medium-scale deployment
Suppose a company with a globally distributed workforce uses Cube Cloud to enable self-serve exploration in multiple BI tools and AI agents; it also uses Cube Cloud to power embedded analytics in its SaaS platform that caters to a vast worldwide customer base.
This organization:
- Uses the Enterprise product tier of Cube Cloud.
- Runs two Production Clusters that are active 24/7 and auto-scale up to 8 API instances during a peak hour every day.
- Operates on a moderate volume of data that requires the usage of 4 Cube Store Workers by both Production Clusters to run queries and refresh pre-aggregations 24/7, being active approximately 50% of the time.
- Uses a dedicated Development Instance for testing purposes that is active 12 hours a day.
- Has a team of 5 data engineers who frequently update the data model, with each data engineer spending about 4 hours a day in the development mode of the dedicated Development Instance.
| Resource | Usage per month | CCU per month |
|---|---|---|
| Production Cluster | 2 Production Clusters × 24 hours per day × 30 days | 1440 hours × 4 CCUs per hour = 5760 CCUs |
| Additional Cube API Instance | 2 Production Clusters × (8 – 2) API Instances × 1 hour per day × 30 days | 360 hours × 1 CCU per hour = 360 CCUs |
| Cube Store Worker | 2 Production Clusters × 4 Cube Store Workers × 12 hours per day × 30 days | 2880 hours × 1 CCU per hour = 2880 CCUs |
| Development Instance | 1 Development Instance × 12 hours per day × 30 days | 360 hours × 1 CCU per hour = 360 CCUs |
| Development Instance (for development mode) | 5 users × 4 hours per day × 30 days | 600 hours × 1 CCU per hour = 600 CCUs |
| Total | 9960 CCUs |
Large-scale deployment
Suppose a company uses Cube Cloud as a mission-critical part of their infrastructure to enable its globally distributed workforce, customer base, and (or) partners to operate at scale.
This organization:
- Uses the Enterprise product tier of Cube Cloud.
- Uses dedicated infrastructure.
- Runs a Production Multi-Cluster that is active 24/7, includes 3 Production Clusters, with each Production Cluster auto-scaling up to 10 API instances during a few peak hours every day.
- Operates on a large volume of data that requires the usage of 16 Cube Store Workers to run queries and refresh pre-aggregations 24/7, being active approximately 50% of the time.
- Uses a dedicated Development Instance for testing purposes that is active 24 hours a day.
- Has a team of 10 data engineers who frequently update the data model, with each data engineer spending about 4 hours a day in the development mode of the dedicated Development Instance.
- Uses a Query History tier with 14-day data retention to inform the work of data engineers.
| Resource | Usage per month | CCU per month |
|---|---|---|
| Dedicated infrastructure | 1 region × 24 hours per day × 30 days | 720 hours × 3 CCUs per hour = 2160 CCUs |
| Production Multi-Cluster | 3 Production Clusters × 24 hours per day × 30 days | 2160 hours × 4 CCUs per hour = 8640 CCUs |
| Additional Cube API Instance | 3 Production Clusters × (10 – 2) API Instances × 4 hours per day × 30 days | 2880 hours × 1 CCU per hour = 2880 CCUs |
| Cube Store Worker | 1 Production Multi-Cluster × 16 Cube Store Workers × 12 hours per day × 30 days | 5760 hours × 1 CCU per hour = 5760 CCUs |
| Development Instance | 1 Development Instance × 24 hours per day × 30 days | 720 hours × 1 CCU per hour = 720 CCUs |
| Development Instance (for development mode) | 10 users × 4 hours per day × 30 days | 1200 hours × 1 CCU per hour = 1200 CCUs |
| Query History (M tier) | 24 hours per day × 30 days | 720 hours × 5 CCUs per hour = 3600 CCUs |
| Total | 24960 CCUs |
Payment terms
Upgrades
You may upgrade your CCUs to a higher-level product tier at any time by paying the difference in per-Cube Consumption Unit pricing, or by asking to convert the price paid for the remaining CCUs into CCUs for the higher product tier at the CCU pricing for that product tier (resulting in a lower number of available CCUs but upgraded to the higher product tier).
Terms
If payment is not received within the contract terms (usually Net-30) or for additional required payment for CCUs exceeding the balance of CCUs in your account, services may degrade or be suspended until new CCUs are purchased.
Future purchases and upgrades are subject to the pricing that is in effect at the time of the order. No credit is allowed for downgrading CCUs to a lower product tier level. Payments are non-refundable.