Updated on 2024-05-13 GMT+08:00

Overview

CloudTable supports pay-per-use and yearly/monthly billing modes to meet user requirements in different scenarios.

  • Pay-per-use is a postpaid billing mode. You pay as you go and just pay for what you use. The fees are calculated by second and settled by hour. This mode allows you to adjust resource usage easily. You do not need to prepare resources in advance, and will not have excessive or insufficient preset resources. Pay-per-use is a good option for scenarios where there are sudden traffic bursts, such as e-commerce promotions.
  • Yearly/monthly: You pay for the cluster by year or month, in advance.
Table 1 Billing modes

Billing Mode

Yearly/Monthly

Pay-per-Use

Payment mode

Prepaid

Billed by the subscription term you purchase.

Postpaid

Billed by the actual CloudTable usage.

Billing usage period

Billed for the required duration specified in your order.

Billed by second and settled by hour.

Billing item

HBase: compute specifications, storage specifications, and node quantity.

ClickHouse: compute specifications, storage specifications, and node quantity.

HBase: compute specifications, storage specifications, and node quantity.

ClickHouse: compute specifications, storage specifications, and node quantity.

Billing mode change

The billing mode cannot be changed from yearly/monthly to pay-per-use.

The billing mode can be changed from pay-per-use to yearly/monthly.

Specification change

  • You can change the node quantity of an HBase cluster.
  • You can change the node quantity of a ClickHouse cluster.

Specifications can be changed, which affects the pricing.

  • You can change the node quantity of an HBase cluster.
  • You can change the compute specifications, storage specifications, and node quantity of a ClickHouse cluster.

Application scenario

A cost-effective option for scenarios where the resource usage duration is predictable. This billing mode is recommended for long-term users.

This mode is ideal when you want more flexibility and control on compute resource usage.