BigQuery Engine for Apache Flink pricing

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BigQuery Engine for Apache Flink is not free to use during the Preview.

Pricing

BigQuery Engine for Apache Flink usage is billed for resources that your BigQuery Engine for Apache Flink jobs consume, including:

  • Compute Slots
  • State storage

In addition, BigQuery Engine for Apache Flink sets up Private Service Connect interfaces (PSC-I) for the managed service to securely connect to data sources and sinks in your consumer VPC, such as your Kafka cluster. In these cases, PSC-I also charges consumer data processing charges to your consumer VPC.

Compute Slot pricing

A BigQuery Engine for Apache Flink Slot is an abstract compute unit that meters compute resources used to run your Flink application. Although the rate for compute pricing is based on the hour, BigQuery Engine for Apache Flink compute usage is billed in per second increments, on a per job basis. Usage is stated in hours in order to apply hourly pricing to second-by-second use. For example, 30 minutes is 0.5 hours. These slots are distinct from BigQuery slots.

When you create a continuous BigQuery Engine for Apache Flink deployment, it provisions and consumes a minimal amount of resources while running, even in the idle state. Customers are billed for those resources. To avoid this cost, delete idle deployments when they're no longer needed.

State storage pricing

The following state storage rate is a monthly rate. It is prorated and billed per second.

When you create a continuous BigQuery Engine for Apache Flink deployment, it provisions and consumes a minimal amount of resources while running, even in the idle state. Customers are billed for those resources. To avoid this cost, delete idle deployments when they're no longer needed.

Guidance on resource usage estimation

It’s recommended that you test your application with production loads to get an accurate estimate of the compute slots and state storage required for your application. The usage can vary based on many factors, including data volume, code complexity, I/O integrations, desired parallelism, state size, and more.

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