Pricing in Cube Cloud

Explains Cube Consumption Units, product tiers, and how Cube Cloud bills for infrastructure and features.

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 and Enterprise product tiers are available on the commit payment plan. Contact us 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 Shared deployments.

You can review its support terms and limits.

Starter

Starter product tier targets low-scale production that is not business-critical.

It offers a Dedicated deployment, 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, 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 Multi-cluster deployments, 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, 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 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, support terms, and limits.

Resources

The following resource types incur CCU consumption and apply to individual resources of deployments within a Cube Cloud account. The consumption is measured in 5-minute intervals.

Resource type	CCUs per hour	Notes
Dedicated deployment	4..8	Depends on a chosen tier
Shared deployment	1..2	Depends on a chosen tier
Cube API Instance	1..2	Depends on a chosen tier
Cube Store Worker	1..2	Depends on a chosen tier
Semantic Catalog	2..4	Depends on a chosen tier
Query History	0..20	Depends on a chosen tier
Monitoring Integrations	1..4	Depends on a chosen tier

The following resource types incur CCU consumption and apply to the whole Cube Cloud account:

Resource type	CCUs per hour	Notes
Single-tenant infrastructure	3	—
Audit Log	4..6	Depends on the chosen tier

The following resource types incur cost and apply to the whole Cube Cloud account:

Resource type	Cost per month	Notes
AI tokens	Varies	Depends on the number of tokens used

Deployment tiers

Dedicated deployments (including individual API instances) and Shared deployments are involved in serving requests through APIs & integrations under the following tiers:

Tier	CCUs per hour	CPU and memory	Dependent features
S	4 — for Dedicated deployment 1 — for Shared deployment 1 — for Cube API Instance	100%	—
M	8 — for Dedicated deployment 2 — for Shared deployment 2 — for Cube API Instance	200%	DAX API

You can upgrade to a chosen tier in the Settings of your deployment. Upgrading to the M tier is only available on the Enterprise product tier.

Cube Store Worker tiers

Cube Store workers are involved in building pre-aggregations and executing queries against them under the following tiers:

Tier	CCUs per hour	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	CCUs per hour	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	Dependent features
XS	1	Up to 10 GB/mo	—
S	2	Up to 25 GB/mo	—
M	4	Up to 50 GB/mo	Query History export

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	CCUs per hour	Dependent features
S	4	—
M	6	Audit Log data export

AI tokens

The price of AI tokens is passed through from the underlying AI service provider without any markup. The cost depends on the number of tokens processed by your Cube Cloud account when using AI features.

You can control the const by setting the token limit on the Billing page of your Cube Cloud account. When the limit is reached, you can increase it to continue using AI features.

Total cost examples

The following examples provide insight into the total cost to use Cube Cloud:

• Small-scale deployment (Dedicated deployment, Premium product tier, S deployment tier).
• Medium-scale deployment (Dedicated deployment with auto-scaling, Enterprise product tier, S deployment tier).
• Large-scale deployment (Multi-cluster deployment with single-tenant infrastructure, Enterprise product tier, M deployment 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 Dedicated deployment (S tier) 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 Shared deployment for testing purposes, with 2 data engineers spending just 1 hour a day each, in the development mode of the Dedicated deployment.

Resource	Usage per month	CCU per month
Dedicated deployment	1 Dedicated deployment × 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
Shared deployment	—	—
Shared deployment (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 Dedicated deployments (S tier) 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 Dedicated deployments to run queries and refresh pre-aggregations 24/7, being active approximately 50% of the time.
• Uses a dedicated Shared deployment (S tier) 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 Shared deployment.

Resource	Usage per month	CCU per month
Dedicated deployment	2 Dedicated deployments × 24 hours per day × 30 days	1440 hours × 4 CCUs per hour = 5760 CCUs
Additional Cube API Instance	2 Dedicated deployments × (8 – 2) API Instances × 1 hour per day × 30 days	360 hours × 1 CCU per hour = 360 CCUs
Cube Store Worker	2 Dedicated deployments × 4 Cube Store Workers × 12 hours per day × 30 days	2880 hours × 1 CCU per hour = 2880 CCUs
Shared deployment	1 Shared deployment × 12 hours per day × 30 days	360 hours × 1 CCU per hour = 360 CCUs
Shared deployment (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 single-tenant infrastructure.
• Runs a Multi-cluster deployment that is active 24/7, includes 3 Dedicated deployments (M tier), with each Dedicated deployment 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 Shared deployment (M tier) 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 Shared deployment.
• Uses a Query History tier with 14-day data retention to inform the work of data engineers.

Resource	Usage per month	CCU per month
Single-tenant infrastructure	1 region × 24 hours per day × 30 days	720 hours × 3 CCUs per hour = 2160 CCUs
Multi-cluster deployment	3 Dedicated deployments × 24 hours per day × 30 days	2160 hours × 8 CCUs per hour = 17280 CCUs
Additional Cube API Instance	3 Dedicated deployments × (10 – 2) API Instances × 4 hours per day × 30 days	2880 hours × 2 CCU per hour = 5760 CCUs
Cube Store Worker	1 Multi-cluster deployment × 16 Cube Store Workers × 12 hours per day × 30 days	5760 hours × 1 CCU per hour = 5760 CCUs
Shared deployment	1 Shared deployment × 24 hours per day × 30 days	720 hours × 2 CCU per hour = 1440 CCUs
Shared deployment (for development mode)	10 users × 4 hours per day × 30 days	1200 hours × 2 CCU per hour = 2400 CCUs
Query History (M tier)	24 hours per day × 30 days	720 hours × 5 CCUs per hour = 3600 CCUs
Total		38400 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.

Troubleshooting

Token limit exceeded

On-demand customers may encounter the following error when their AI usage exceeds the limit set for their Cube Cloud account: Token limit exceeded. Please purchase or allocate more tokens.

To resolve this issue, a user with administrative permissions needs to increase the limit for the AI token consumption at the Billing page of their Cube Cloud account.