BigQuery is a serverless data analytics platform. You don't need to provision individual instances or virtual machines to use BigQuery. Instead, BigQuery automatically allocates computing resources as you need them. You can also reserve compute capacity ahead of time in the form of slots, which represent virtual CPUs. The pricing structure of BigQuery reflects this design.
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BigQuery pricing has two main components:
Compute pricing is the cost to process queries, including SQL queries, user-defined functions, scripts, and certain data manipulation language (DML) and data definition language (DDL) statements.
Storage pricing is the cost to store data that you load into BigQuery.
BigQuery charges for other operations, including using BigQuery Omni, BigQuery ML, BI Engine, and streaming reads and writes.
In addition, BigQuery has free operations and a free usage tier.
Every project that you create has a billing account attached to it. Any charges incurred by BigQuery jobs run in the project are billed to the attached billing account. BigQuery storage charges are also billed to the attached billing account. You can view BigQuery costs and trends by using the Cloud Billing reports page in the Google Cloud console.
Key Point:Pricing models apply to accounts, not individual projects, unless otherwise specified.
BigQuery offers a choice of two compute pricing models for running queries:
On-demand pricing (per TiB). With this pricing model, you are charged for the number of bytes processed by each query. The first 1 TiB of query data processed per month is free.
Capacity pricing (per slot-hour). With this pricing model, you are charged for compute capacity used to run queries, measured in slots (virtual CPUs) over time. This model takes advantage of BigQuery editions. You can use the BigQuery autoscaler or purchase slot commitments, which are dedicated capacity that is always available for your workloads, at a lower price.
For more information about which pricing to choose for your workloads, see Workload management using Reservations.
By default, queries are billed using the on-demand (per TiB) pricing model, where you pay for the data scanned by your queries.
With on-demand pricing, you will generally have access to up to 2,000 concurrent slots, shared among all queries in a single project. Periodically, BigQuery will temporarily burst beyond this limit to accelerate smaller queries. In addition, you might occasionally have fewer slots available if there is a high amount of contention for on-demand capacity in a specific location.
On-demand (per TiB) query pricing is as follows:
If you pay in a currency other than USD, the prices listed in your currency on Cloud Platform SKUs apply.
Note the following regarding on-demand (per TiB) query charges:
LIMIT on the results.BigQuery provides cost control mechanisms that enable you to cap your query costs. You can set:
For detailed examples of how to calculate the number of bytes processed, see Query size calculation.
BigQuery offers a capacity-based analysis pricing model for customers who prefer a predictable cost for queries rather than paying the on-demand price per TiB of data processed.
To enable capacity pricing, use BigQuery Reservations.
BigQuery editions
BigQuery editions offer pay as you go pricing (with autoscaling) and optional one year and three year commitments. With editions, you consume query processing capacity, measured in slots, rather than being billed for bytes processed.
BigQuery editions slot capacity:
Optional BigQuery editions slot commitments:
The following table shows the cost of slots in Standard edition.
The following table shows the cost of slots in Enterprise edition.
The following table shows the cost of slots in Enterprise plus edition.
If you pay in a currency other than USD, the prices listed in your currency on Cloud Platform SKUs apply.
Storage pricing is the cost to store data that you load into BigQuery. You pay for active storage and long-term storage.
Active storage includes any table or table partition that has been modified in the last 90 days.
Long-term storage includes any table or table partition that has not been modified for 90 consecutive days. The price of storage for that table automatically drops by approximately 50%. There is no difference in performance, durability, or availability between active and long-term storage.
The first 10 GiB of storage per month is free.
If you pay in a currency other than USD, the prices listed in your currency on Cloud Platform SKUs apply.
See the physical storage documentation for eligibility criteria.
Storage pricing is based on the amount of data stored in your tables, temporary session tables and temporary multi-statement tables. There are no storage charges for temporary cached query result tables.
The size of the data is calculated based on the data types of the individual columns. For a detailed explanation of how data size is calculated, see Data size calculation.
Storage pricing is prorated per MiB, per second. For example, if you are using active logical storage in us-central1:
Storage usage is calculated in gibibytes months (GiB months), where 1 GiB is 230 bytes (1,024 MiB). Similarly, 1 tebibyte (TiB) is 240 bytes (1,024 GiB). The final usage value is the product of data size in gibibytes and storage use time in months.
If the data in a table is not modified or deleted within 90 consecutive days, it is billed at the long-term storage rate. There is no degradation of performance, durability, availability, or any other functionality when a table is considered long-term storage.
Each partition of a partitioned table is considered separately for long-term storage pricing. If a partition hasn't been modified in the last 90 days, the data in that partition is considered long term storage and is charged at the discounted price.
If the table is edited, the price reverts back to the regular storage pricing, and the 90-day timer starts counting from zero. Anything that modifies the data in a table resets the timer, including:
Action Details Loading data into a table Any load or query job that appends data to a destination table or overwrites a destination table. Copying data into a table Any copy job appends data to a destination table or overwrites a destination table. Writing query results to a table Any query job that appends data to a destination table or overwrites a destination table. Using data manipulation language (DML) Using a DML statement to modify table data. Using data definition language (DDL) Using aCREATE OR REPLACE TABLE statement to replace a table.
Streaming data into the table
Ingesting data using the tabledata.insertAll API call.
All other actions do not reset the timer, including the following:
For tables that reach the 90-day threshold during a billing cycle, the price is prorated accordingly.
Long-term storage pricing applies only to BigQuery storage, not to data stored in external data sources such as Bigtable, Cloud Storage, and Google Drive.
When you load data into BigQuery or query the data, you're charged according to the data size. Data size is calculated based on the size of each column's data type.
The size of your stored data and the size of the data processed by your queries is calculated in gibibytes (GiB), where 1 GiB is 230 bytes (1,024 MiB). Similarly, 1 tebibyte (TiB) is 240 bytes (1,024 GiB).
For more information, see Data type sizes.
The BigQuery Data Transfer Service charges monthly on a prorated basis. You are charged as follows:
1. After data is transferred to BigQuery, standard BigQuery storage and query pricing applies.
2. Extraction, uploading to a Cloud Storage bucket, and loading data into BigQuery is free.
3. Costs can be incurred outside of Google Cloud by using the BigQuery Data Transfer Service, such as AWS or Azure data transfer charges.
4. Data is not automatically deleted from your Cloud Storage bucket after it is uploaded to BigQuery. Consider deleting the data from your Cloud Storage bucket to avoid additional storage costs. See Cloud Storage pricing.
5. Costs apply for connectors provided by third-party partners. The pricing model differs for different partners and connectors. For more pricing details, refer to individual connectors when enrolling in Marketplace.
Every Android app has a unique application ID that looks like a Java package name, such as com.example.myapp. The Installs report contains a column of "Package Name". The number of unique package names is used for calculating usage of transfers.
Each transfer you create generates one or more runs per day. Package names are only counted on the day a transfer run completes. For example, if a transfer run begins on July 14th but completes on July 15th, the package names are counted on July 15th.
If a unique package name is encountered in more than one transfer run on a particular day, it is counted only once. Package names are counted separately for different transfer configurations. If a unique package name is encountered in runs for two separate transfer configurations, the package name is counted twice.
If a package name appeared every day for an entire month, you would be charged the full $25 for that month. Otherwise, if it appeared for a part of the month, the charge would be prorated.
Example#1: If we sync for 1 application - com.smule.singandroid, will it cost us $25 per month + storage price for BigQuery?
The answer is $25 per month (prorated) + storage/querying costs from BigQuery.
Example#2: If we sync all historic data (for 10 years), will we be charged for 120 months or for 1 month, because we transferred them at once?
The answer is still $25 per month (prorated) + storage/querying costs from BigQuery, since we charge $25 per unique Package Name in the Installs_country table, regardless of how many years the historic data goes back to for that unique Package Name.
BigQuery Omni offers the following pricing models depending on your workloads and needs.
On-Demand compute pricing
Similar to BigQuery on-demand analysis model, BigQuery Omni queries, by default are billed using the on-demand (per TiB) pricing model, where you pay for the data scanned by your queries.
With on-demand pricing, you will generally have access to a large pool of concurrent slots, shared among all queries in a single project. Periodically, BigQuery Omni will temporarily burst beyond this limit to accelerate smaller queries. In addition, you might occasionally have fewer slots available if there is a high amount of contention for on-demand capacity in a specific location.
BigQuery Omni on-demand (per TiB) query pricing is as follows:
Region Price per TiB AWS North Virginia (aws-us-east-1) $7.82 Azure North Virginia (azure-eastus2) $9.13 AWS Seoul (aws-ap-northeast-2) $10.00 AWS Oregon (aws-us-west-2) $7.82 AWS Ireland (aws-eu-west-1) $8.60 AWS Sydney (aws-ap-southeast-2) $10.55 AWS Frankfurt (aws-eu-central-1) $10.16If you pay in a currency other than USD, the prices listed in your currency on Cloud Platform SKUs apply.
Pricing details
The details and limitations are similar to BigQuery analysis pricing. Note the following regarding on-demand (per TiB) query charges:
LIMIT
on the results.BigQuery provides cost control mechanisms that enable you to cap your query costs. You can set:
BigQuery Omni with editions
BigQuery Omni regions support BigQuery editions. At present only Enterprise Edition is supported in Omni regions
The following table shows the cost of slots in Omni regions
AWS North Virginia (aws-us-east-1)
Commitment model Hourly cost Number of slots PAYG (no commitment) $7.50 (billed per second with a 1 minute minimum) 100 1 yr commit $6 (billed for 1 year) 100 3 yr commit $4.50 (billed for 3 years) 100Azure North Virginia (azure-eastus2)
Commitment model Hourly cost Number of slots PAYG (no commitment) $8.80 (billed per second with a 1 minute minimum) 100 1 yr commit $7 (billed for 1 year) 100 3 yr commit $5.30 (billed for 3 years) 100AWS Seoul (aws-ap-northeast-2)
Commitment model Hourly cost Number of slots PAYG (no commitment) $9.60 (billed per second with a 1 minute minimum) 100 1 yr commit $7.7 (billed for 1 year) 100 3 yr commit $5.80 (billed for 3 years) 100AWS Oregon (aws-us-west-2)
Commitment model Hourly cost Number of slots PAYG (no commitment) $7.50 (billed per second with a 1 minute minimum) 100 1 yr commit $6.00 (billed for 1 year) 100 3 yr commit $4.50 (billed for 3 years) 100AWS Ireland (aws-eu-west-1)
Commitment model Hourly cost Number of slots PAYG (no commitment) $8.25 (billed per second with a 1 minute minimum) 100 1 yr commit $6.60 (billed for 1 year) 100 3 yr commit $4.95 (billed for 3 years) 100AWS Sydney (aws-ap-southeast-2)
Commitment model Hourly cost Number of slots PAYG (no commitment) $10.13 (billed per second with a 1 minute minimum) 100 1 yr commit $8.10 (billed for 1 year) 100 3 yr commit $6.08 (billed for 3 years) 100AWS Frankfurt (aws-eu-central-1)
Commitment model Hourly cost Number of slots PAYG (no commitment) $9.75 (billed per second with a 1 minute minimum) 100 1 yr commit $7.80 (billed for 1 year) 100 3 yr commit $5.85 (billed for 3 years) 100Omni Cross Cloud Data Transfer
When using Omni&#;s Cross Cloud capabilities (Cross Cloud Transfer, Create Table as Select, Insert Into Select, Cross Cloud Joins, and Cross Cloud Materialized Views) that involve data moving from AWS or Azure to Google Cloud, there will be additional charges for data transfer.
Specifically for Cross-Cloud Materialized Views, Create Table as Select, Insert Into Select, and Cross Cloud Joins there are no charges during Preview. Starting 29 February , these services will be generally available and you will be charged for data transfer. You will be charged for data transfer only when using any of the above listed services from an AWS or Azure region to a Google Cloud BigQuery region. You will be charged on a per GiB rate based on the amount of data transferred from AWS or Azure to Google Cloud.
SKU Billing model Meter List price Cross-cloud data transfer from AWS North Virginia (aws-us-east-1) to Google Cloud North America usage-based GiB transferred $.09 Cross-cloud data transfer from Azure North Virginia (azure-eastus2) to Google Cloud North America usage-based GiB transferred $. Cross-cloud data transfer from AWS Seoul (aws-ap-northeast-2) to Google Cloud Asia usage-based GiB transferred $.126 Cross-cloud data transfer from AWS Oregon (aws-us-west-2) to Google Cloud North America usage-based GiB transferred $.09 Cross-cloud data transfer from AWS Ireland (aws-eu-west-1) to Google Cloud Europe usage-based GiB transferred $.09 Cross-cloud data transfer from AWS Sydney (aws-ap-southeast-2) to Google Cloud Oceania usage-based GiB transferred $.114 Cross-cloud data transfer from AWS Frankfurt (aws-eu-central-1) to Google Cloud Europe usage-based GiB transferred $.09Omni Managed Storage
When using Omni&#;s Cross Cloud Materialized Views capability, you will also be charged for creation of local materialized views which is on BigQuery Managed Storage on AWS. You will be charged a per GiB for the amount of physical storage that is used for the local materialized view.
Operation Pricing Active physical storage (aws-us-east-1) $0.05 per GiB per month Long-term physical storage (aws-us-east-1) $0.025 per GiB per month Active physical storage (azure-eastus2) $0.05 per GiB per month Long-term physical storage (azure-eastus2) $0.025 per GiB per month Active physical storage (aws-ap-northeast-2) $0.052 per GiB per month Long-term physical storage (aws-ap-northeast-2) $0.026 per GiB per month Active physical storage (aws-us-west-2) $0.04 per GiB per month Long-term physical storage (aws-us-west-2) $0.02 per GiB per month Active physical storage (aws-eu-west-1) $0.044 per GiB per month Long-term physical storage (aws-eu-west-1) $0.022 per GiB per month Active physical storage (aws-ap-southeast-2) $0.052 per GiB per month Long-term physical storage (aws-ap-southeast-2) $0.026 per GiB per month Active physical storage (aws-eu-central-1) $0.052 per GiB per month Long-term physical storage (aws-eu-central-1) $0.026 per GiB per monthBigQuery offers two modes of data ingestion:
Batch loading. Load source files into one or more BigQuery tables in a single batch operation.
Streaming. Stream data one record at a time or in small batches using the BigQuery Storage Write API or the legacy streaming API.
For more information about which mode to choose, see Introduction to loading data.
If you pay in a currency other than USD, the prices listed in your currency on Cloud Platform SKUs apply.
By default, you are not charged for batch loading data from Cloud Storage or from local files into BigQuery. Load jobs by default use a shared pool of slots. BigQuery does not make guarantees about the available capacity of this shared pool or the throughput you will see. Alternatively, you can purchase dedicated slots to run load jobs. You are charged capacity-based pricing for dedicated slots. When load jobs are assigned to a reservation, they lose access to the free pool. For more information, see Assignments.
Once your data is loaded into BigQuery, it is subject to BigQuery storage pricing. If you load data from Cloud Storage, you are charged for storing the data in Cloud Storage. For details, see Data storage on the Cloud Storage pricing page.
BigQuery offers the following modes of data extraction:
Batch export. Use an an extract job to export table data to Cloud Storage. There is no processing charge for exporting data from a BigQuery table using an extract job.
Export query results. Use the EXPORT DATA
statement to export query results to Cloud Storage
or Bigtable.
You are billed for processing the query statement using the on-demand or capacity
based model.
Streaming reads. Use the Storage Read API to perform high-throughput reads of table data. You are billed for the amount of data read.
You are not charged for data extraction or data transfer when accessing query results in the Google Cloud console, BigQuery API, or any other clients, such as Looker.
If you pay in a currency other than USD, the prices listed in your currency on Cloud Platform SKUs apply.
You are charged for data transfer when you export data in batch from BigQuery to a Cloud Storage bucket or Bigtable table in another region, as follows:
Case Example Rate Export within the same location From us-east1 to us-east1 Free Export from BigQuery US multi-region From US multi-region to us-central1 (Iowa) Free Export from BigQuery US multi-region From US multi-region to any region (except us-central1 (Iowa)) See following table Export from BigQuery EU multi-region From EU multi-region to europe-west4 (Netherlands) Free Export from BigQuery EU multi-region From EU multi-region to any region (except europe-west4 (Netherlands)) See following table Export across locations From us-east1 to us-central1 See following table Note:All prices are in $/GiB and all GiB are in physical bytes.
Source location Destination location Northern America Europe Asia Indonesia Oceania Middle East Latin America Africa Northern America $0.02/GiB $0.05/GiB $0.08/GiB $0.10/GiB $0.10/GiB $0.11/GiB $0.14/GiB $0.11/GiB Europe $0.05/GiB $0.02/GiB $0.08/GiB $0.10/GiB $0.10/GiB $0.11/GiB $0.14/GiB $0.11/GiB Asia $0.08/GiB $0.08/GiB $0.08/GiB $0.10/GiB $0.10/GiB $0.11/GiB $0.14/GiB $0.11/GiB Indonesia $0.10/GiB $0.10/GiB $0.10/GiB $0.08/GiB $0.08/GiB $0.11/GiB $0.14/GiB $0.14/GiB Oceania $0.10/GiB $0.10/GiB $0.10/GiB $0.08/GiB $0.08/GiB $0.11/GiB $0.14/GiB $0.14/GiB Middle East $0.11/GiB $0.11/GiB $0.11/GiB $0.11/GiB $0.11/GiB $0.08/GiB $0.14/GiB $0.11/GiB Latin America $0.14/GiB $0.14/GiB $0.14/GiB $0.14/GiB $0.14/GiB $0.14/GiB $0.14/GiB $0.14/GiB Africa $0.11/GiB $0.11/GiB $0.11/GiB $0.14/GiB $0.14/GiB $0.11/GiB $0.14/GiB $0.11/GiBus-east1 to us-east1us to us-east1eu to europe-west1us-east1 to northamerica-northeast1
europe-west1 to europe-north1us to asiaeurope-west1 to southamerica-east1
us to australia-southeast1australia-southeast1 to europe-west1
If you pay in a currency other than USD, the prices listed in your currency on Cloud Platform SKUs apply.
If you pay in a currency other than USD, the prices listed in your currency on Cloud Platform SKUs apply.
The Storage Read API has an on-demand price model. With on-demand pricing, BigQuery charges for the number of bytes processed (also referred to as bytes read). On-demand pricing is solely based on usage, with a bytes read free tier of 300 TiB per month for each billing account. Bytes scanned as part of reads from temporary tables are free and do not count against the 300TiB free tier. This free bytes read 300 TiB is on the bytes-read component, and does not apply to associated outbound data transfer.
Note the following regarding Storage Read API charges:
ReadRows call
fails.ReadRows call before the end of the stream is reached, you
are charged for any data read before the cancellation. Your charges can
include data that was read but not returned to you before the cancellation of
the ReadRows call.WHERE clause to prune
partitions. For more information, see
Querying partitioned tables.BigQuery offers two modes of replicating (copying) data between regions:
Cross-region copy. One time or scheduled copy of table data to between regions or multi-regions, see copy datasets or copy tables.
Cross-region replication. Ongoing, incremental replication of a dataset between two or more different regions or multi-regions, see cross-region dataset replication.
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Cross-region Turbo replication. High performance, ongoing, incremental replication of a dataset between two or more different regions or multi-regions. Available only with managed disaster recovery.
Replicated data stored in the destination region or multi-region is charged according to BigQuery storage pricing.
You are charged for data transfer for the volume of data replicated. The use cases and breakdown of data transfer charges are provided as follows:
Case Example Rate Replicate within the same location From us-east1 to us-east1 Free Replicate from BigQuery US multi-region From US multi-region to us-central1 (Iowa) Free Replicate from BigQuery US multi-region From US multi-region to any region (except us-central1 (Iowa)) See following table Replicate from BigQuery EU multi-region From EU multi-region to europe-west4 (Netherlands) Free Replicate from BigQuery EU multi-region From EU multi-region to any region (except europe-west4 (Netherlands)) See following table Replicate across locations From us-east1 to us-central1 See following table Note:All prices are in $/GiB and all GiB are in physical bytes.
Source location Destination location Northern America Europe Asia Indonesia Oceania Middle East Latin America Africa Northern America $0.02/GiB $0.05/GiB $0.08/GiB $0.10/GiB $0.10/GiB $0.11/GiB $0.14/GiB $0.11/GiB Europe $0.05/GiB $0.02/GiB $0.08/GiB $0.10/GiB $0.10/GiB $0.11/GiB $0.14/GiB $0.11/GiB Asia $0.08/GiB $0.08/GiB $0.08/GiB $0.10/GiB $0.10/GiB $0.11/GiB $0.14/GiB $0.11/GiB Indonesia $0.10/GiB $0.10/GiB $0.10/GiB $0.08/GiB $0.08/GiB $0.11/GiB $0.14/GiB $0.14/GiB Oceania $0.10/GiB $0.10/GiB $0.10/GiB $0.08/GiB $0.08/GiB $0.11/GiB $0.14/GiB $0.14/GiB Middle East $0.11/GiB $0.11/GiB $0.11/GiB $0.11/GiB $0.11/GiB $0.08/GiB $0.14/GiB $0.11/GiB Latin America $0.14/GiB $0.14/GiB $0.14/GiB $0.14/GiB $0.14/GiB $0.14/GiB $0.14/GiB $0.14/GiB Africa $0.11/GiB $0.11/GiB $0.11/GiB $0.14/GiB $0.14/GiB $0.11/GiB $0.14/GiB $0.11/GiBAll prices are in $/GiB and all GiB are in physical bytes.
Source location Destination location Northern America Europe Asia Indonesia Oceania Middle East Latin America Africa Northern America $0.04/GiB $0.10/GiB $0.16/GiB $0.20/GiB $0.20/GiB $0.22/GiB $0.28/GiB $0.22/GiB Europe $0.10/GiB $0.04/GiB $0.16/GiB $0.20/GiB $0.20/GiB $0.22/GiB $0.28/GiB $0.22/GiB Asia $0.16/GiB $0.16/GiB $0.16/GiB $0.20/GiB $0.20/GiB $0.22/GiB $0.28/GiB $0.22/GiB Indonesia $0.20/GiB $0.20/GiB $0.20/GiB $0.16/GiB $0.16/GiB $0.22/GiB $0.28/GiB $0.28/GiB Oceania $0.20/GiB $0.20/GiB $0.20/GiB $0.16/GiB $0.16/GiB $0.22/GiB $0.28/GiB $0.28/GiB Middle East $0.22/GiB $0.22/GiB $0.22/GiB $0.22/GiB $0.22/GiB $0.16/GiB $0.28/GiB $0.22/GiB Latin America $0.28/GiB $0.28/GiB $0.28/GiB $0.28/GiB $0.28/GiB $0.28/GiB $0.28/GiB $0.28/GiB Africa $0.22/GiB $0.22/GiB $0.22/GiB $0.28/GiB $0.28/GiB $0.22/GiB $0.28/GiB $0.22/GiBBigQuery can leverage external services to help with data analytics workflows. For some of these services external to BigQuery, you will still be charged with BigQuery SKUs:
BigQuery Studio Notebooks rely on a default notebook runtime that uses Colab Enterprise runtime to allow notebook code execution. Usage of these services are billed as pay-as-you go slots and GB/s usage for SSD. You can expect to see charges for BigQuery notebooks on or after April 20th.
The default notebook runtime is a Google-provisioned virtual machine (VM) that can run the code in your notebook (IPYNB file). This allows BigQuery customers to execute python script and is not charged after idle time.
*The Pay as you go slots, will be metered in the edition that is being used at the project level.
The default notebook allocates PD and SSD in the background to help users install new data science packages and maintain their work beyond the Python code they execute. Once the PD and SSD is released, you will not see charges.
BigQuery Studio notebook pricing details:
BigQuery ML models can be classified into two different categories: built-in models and external models. BigQuery ML built-in models are trained within BigQuery, such as linear regression, logistic regression, means, matrix factorization, PCA and time series models (e.g., ARIMA_PLUS). BigQuery ML external models are trained utilizing other Google Cloud services, DNN, boosted tree and random forest (which are trained on Vertex AI) and AutoML models (which are trained on the Vertex AI Tables backend). BigQuery ML model training pricing is based on the model type as well as your usage pattern: editions or on-demand. BigQuery ML prediction and evaluation functions are executed within BigQuery ML for all model types, priced as explained below.
BigQuery ML is available in Enterprise and Enterprise Plus Editions for customers who prefer a compute capacity (number of slots) based pricing model over the on-demand (number of bytes processed) model. Customers can use Enterprise or Enterprise Plus reservations to use all features of BigQuery ML. BigQuery ML usage will be included in the BigQuery Editions usage.
BigQuery has three job types for reservation assignment: QUERY,
PIPELINE, and ML_EXTERNAL. QUERY assignments, which are used for
analytical queries, are also used to run CREATE MODEL queries for
BigQuery ML built-in models. Built-in model training and analytical
queries share the same pool of resources in their assigned reservations, and
have the same behavior regarding being preemptible, and using idle slots from
other reservations.
Because external models are trained outside of BigQuery, these
workloads are not preemptible. As a result, to ensure other workloads are not
impacted, only reservations with ML_EXTERNAL job type assignment can be used
for these external jobs. Reservations workload
management
describes how to create reservations for external model training jobs. The slots
usage per job is calculated to maintain the price parity between
BigQuery slots and external Google Cloud service costs.
You can add a ML_EXTERNAL job type assignment to reservations that you
want to use for building BigQuery ML external models. When slots in the
reservation are shared by both QUERY/PIPELINE and ML_EXTERNAL jobs,
QUERY/PIPELINE jobs can use the slots only when they are available.
Thus, it is important to ensure all critical QUERY and PIPELINE jobs
run in their own reservations, as ML_EXTERNAL jobs are not preemptible.
ML_EXTERNAL jobs cannot use idle slots from other reservations. On the other hand,
if slots in this reservation (with ML_EXTERNAL assignment) are available, jobs
from other reservations (with ignore_idle_slots=false) can use them.
ML_EXTERNAL slots. The number of slots is subject to change based on
ML_EXTERNAL reservations.To create an AutoML Tables model, you need approximately slots. The number of slots is subject to change based on Vertex AI Tables backend pricing. Meanwhile, the number of external slots used to train other BigQuery ML external models (such as DNN, Boosted Tree, Random Forest etc.) is dynamically determined in order to scale the training job horizontally. More specifically, the Vertex AI training scale tier (Virtual Machine configurations for chief worker, parameter servers and workers) is determined at runtime based on the training data size and model type. The BigQuery ML service then reserves a number of slots equivalent to the total VM price from yourreservations.
BigQuery ML pricing for on-demand queries depends on the type of operation: model type, model creation, model evaluation, model inspection, or model prediction.
Note:Matrix factorization models are only available to editions customers or customers with reservations
BigQuery ML on-demand pricing is as follows:
If you pay in a currency other than USD, the prices listed in your currency on Cloud Platform SKUs apply.1 The CREATE MODEL statement stops at 50 iterations
for iterative models. This applies to both on-demand and editions pricing.
2 For time series models, when auto-arima is enabled for
automatic hyper-parameter tuning, multiple candidate models are fitted and
evaluated during the training phase. In this case, the number of bytes
processed by the input SELECT statement is multiplied by the
number of candidate models, which can be controlled by the
AUTO_ARIMA_MAX_ORDER
training option for ARIMA_PLUS or the AUTO_ARIMA_MAX_ORDER
training option for ARIMA_PLUS_XREG. This applies to both on-demand and editions pricing.
The following notes apply to time series model creation:
For single time series forecasting with auto-arima enabled,
when AUTO_ARIMA_MAX_ORDER is (1, 2, 3, 4, 5), the number
of candidate models is (6, 12, 20, 30, 42) respectively if non-seasonal
d equals one; otherwise, the number of candidate models is
(3, 6, 10, 15, 21).
For multiple time series forecasting using
TIME_SERIES_ID_COL, the charge is for (6, 12, 20, 30, 42)
candidate models when AUTO_ARIMA_MAX_ORDER is
(1, 2, 3, 4, 5) respectively.
Note that this model selection only applies to model creation. For model evaluation, inspection, and prediction, only the selected model is used, with regular query pricing.
3 See BigQuery ML Remote Model Inference for details.
BigQuery ML lets customers create a remote model that targets a Vertex AI foundation model, a Vertex AI online prediction endpoint, or a Cloud AI API, for example Cloud AI Vision API.
The pricing for BigQuery ML remote model inference has the following parts:
For remote endpoint model pricing, there will be a separate bill from the above services. You may use the billing label billing_service = 'bigquery_ml' and the billing label bigquery_job_id to filter the exact charges.
When using supervised tuning with remote models over Vertex AI LLMs, costs are calculated based on the following:
AS SELECT clause.
These charges are billed from BigQuery to your project.Due to the nature of the underlying algorithms of some model types and differences in billing, the bytes processed will not be calculated for some model types until after training is completed due to the complexity of calculating the initial estimate.
BigQuery ML charges are not itemized separately on your billing statement. For current models, if you have BigQuery Editions, BigQuery ML charges are included.
If you are using on-demand pricing, BigQuery ML charges are included in the BigQuery analysis (query) charges.
BigQuery ML jobs that perform inspection, evaluation, and prediction
operations incur the same charges as on-demand query jobs. Because CREATE MODEL
queries incur different charges, you must calculate CREATE MODEL job costs
independently by using the Cloud logging audit logs. Using the audit logs, you can
determine the bytes billed by the BigQuery ML service for each
BigQuery ML CREATE MODEL job. Then, multiply the bytes billed by the
appropriate cost for CREATE MODEL queries in your regional or multi-regional
location.
For example, to determine the cost of a query job in the US that includes a
BigQuery ML CREATE MODEL statement:
Open the Cloud Logging page in the Google Cloud console.
Verify that the product is set to BigQuery.
Click the drop-down arrow in the "Filter by label or text search" box and choose Convert to advanced filter. This adds the following text to the filter:
resource
.
type
=
"bigquery_resource"
Add the following text on line two below the resource.type line:
protoPayload
.
serviceData
.
jobCompletedEvent
.
job
.
jobConfiguration
.
query
.
statementType
=
"CREATE_MODEL"
To the right of the Submit Filter button, choose the appropriate time
frame from the drop-down list. For example, choosing Last 24 hours would
display BigQuery ML CREATE MODEL jobs completed in the past 24 hours.
Click Submit Filter to display the jobs completed in the given time window.
After the data is populated, click View Options and choose Modify custom fields.
In the Add custom fields dialog, enter:
protoPayload
.
serviceData
.
jobCompletedEvent
.
job
.
jobStatistics
.
totalBilledBytes
Click Save to update the results.
To calculate the charges for the BigQuery ML CREATE MODEL job, multiply
the bytes billed by the BigQuery ML on-demand price.
In this example, the CREATE MODEL job processed bytes. To
calculate the cost of this job in the US multi-regional location, divide
the billed bytes by the number of bytes per TiB, and multiply it by the model
creation cost:
/ x $312.5 = $28.669
Currently, Cloud logging metrics are not available for BigQuery ML. When available, Cloud logging metrics will allow you to view BigQuery ML bytes billed in graphs with custom aggregations.
BI Engine accelerates SQL queries by caching BigQuery data in memory. The amount of data stored is constrained by the amount of capacity you purchase. To purchase BI Engine capacity, create a BI Engine reservation in the project where queries will be run.
When BI Engine accelerates a query, the query stage that reads table data is free. Subsequent stages depend on the type of BigQuery pricing you're using:
For on-demand pricing, stages that use BI Engine are charged for 0 scanned bytes. Subsequent stages will not incur additional on-demand charges.
For editions pricing, the first stage consumes no BigQuery reservation slots. Subsequent stages use slots from the BigQuery reservation.
BI Engine pricing is as follows:
If you pay in a currency other than USD, the prices listed in your currency on Cloud Platform SKUs apply.When you are using BigQuery capacity compute pricing with BigQuery editions commitments, you are eligible to receive a limited amount of BI Engine capacity as part of your editions price, at no extra cost, as shown in the following chart. To receive BI Engine capacity at no additional cost, follow the instructions to reserve capacity in a project within the same organization as your editions reservation. To ensure a particular project&#;s BI Engine reservation is discounted toward this bundled capacity, there should be some slots assigned to the project. BI Engine reservation in an 'on-demand analysis' project will not be counted towards the free capacity. Free capacity is shown in your Billing Reports as a normal cost, but it is discounted as a "Spending-Based Discount".
Number of slots purchased No-cost, additional BI Engine capacity (GiB) 100 5 500 25 50 75 100 (maximum per organization)The following BigQuery operations are free of charge in every location. Quotas and limits apply to these operations.
Operation Details Load data Free using the shared slot pool. Customers can choose editions pricing for guaranteed capacity. Once the data is loaded into BigQuery, you are charged for storage. For details, see Data ingestion editions pricing. Copy data You are not charged for copying a table, but you do incur charges Data ingestion editions pricing or storing the new table and the table you copied. For more information, see Copying an existing table. Export data Free using the shared slot pool, but you do incur charges for storing the data in Cloud Storage. Customers can choose editions pricing for guaranteed capacity. When you use the EXPORT DATA SQL statement, you are charged for query processing. For details, see Exporting data. Delete operations You are not charged for deleting datasets or tables, deleting individual table partitions, deleting views, or deleting user-defined functions Metadata operations You are not charged for list, get, patch, update and delete calls. Examples include (but are not limited to): listing datasets, updating a dataset's access control list, updating a table's description, or listing user-defined functions in a dataset. Metadata caching operations for BigLake tables aren't included in free operations.As part of the Google Cloud Free Tier, BigQuery offers some resources free of charge up to a specific limit. These free usage limits are available during and after the free trial period. If you go over these usage limits and are no longer in the free trial period, you will be charged according to the pricing on this page. You can try BigQuery's free tier in the BigQuery sandbox without a credit card.
Resource Monthly free usage limits Details Storage The first 10 GiB per month is free. BigQuery ML models and training data stored in BigQuery are included in the BigQuery storage free tier. Queries (analysis) The first 1 TiB of query data processed per month is free.BigQuery Editions pricing is also available for high-volume customers that prefer a stable, monthly cost.
BI Engine Up to 1 GiB of capacity for Looker Studio users without configuring a BI Engine reservation. This capacity is available to Looker Studio users that don't use BigQuery native Looker Studio integration. This additional capacity is provided on best-effort basis.The BigQuery flat-rate pricing model is no longer offered as of July 5, . It is described here for customers who have existing flat-rate commitments.
When you use the flat-rate compute pricing model, you purchase dedicated query processing capacity, measured in BigQuery slots. Your queries consume this capacity, and you are not billed for bytes processed. If your capacity demands exceed your committed capacity, BigQuery will queue up queries, and you will not be charged additional fees.
Flat-rate compute pricing:
The following table shows the cost of your monthly flat-rate slot commitment. For more information, see Monthly commitments.
If you pay in a currency other than USD, the prices listed in your currency on Cloud Platform SKUs apply.
The following table shows the cost of your annual flate-rate slot commitment. For more information, see Annual commitments.
If you pay in a currency other than USD, the prices listed in your currency on Cloud Platform SKUs apply.
Flex slots are a special commitment type:
Flex slots are subject to capacity availability. When you attempt to purchase flex slots, success of this purchase is not guaranteed. However, once your commitment purchase is successful, your capacity is guaranteed until you cancel it. For more information, see flex slots.
The following table shows the cost of your Flex slot commitment.
BigQuery Omni offers flat-rate pricing which provides a predictable cost for queries. To enable flat-rate pricing, use BigQuery Reservations.
When you enroll in flat-rate pricing for BigQuery Omni, you purchase dedicated query processing capacity, measured in slots, on Amazon Web Services or Microsoft Azure. Your queries consume this capacity, and you are not billed for bytes processed.
BigQuery Omni flat-rate pricing:
The following table shows the cost of your monthly slot commitment. For more information, see Monthly commitments.
The following table shows the cost of your annual slot commitment. For more information, see Annual commitments.
Flex slots are a special commitment type:
Flex slots on BigQuery Omni are subject to capacity availability on AWS or Azure. When you attempt to purchase flex slots, success of this purchase is not guaranteed. However, once your commitment purchase is successful, your capacity is guaranteed until you cancel it. For more information, see flex slots.
The following table shows the cost of your Flex slot commitment.
When you are using BigQuery flat-rate slot commitments, you are eligible to receive a limited amount of BI Engine capacity as part of your flat-rate price, at no extra cost, as shown in the following chart. To receive BI Engine capacity at no additional cost, follow the instructions to reserve capacity in a project within the same organization as your flat-rate reservation. To ensure a particular project's BI Engine reservation is discounted toward this bundled capacity, there should be some slots assigned to the project. A BI Engine reservation in an on-demand compute project don't counted towards free capacity. Free capacity is shown in your billing reports as a normal cost, but it is discounted as a "Spending-Based Discount".
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Number of slots purchased No-cost, additional BI Engine capacity (GiB) 100 5 500 25 50 75 100 (maximum per organization)