BigQuery Pricing in 2024

Please note that all prices listed herein are as of September 4, 2024 and are subject to change without notice.

Google provides two primary BigQuery pricing models for processing data in its serverless warehouse — namely, on-demand and capacity-based. Before we move forward, let’s understand the measurement units used by the company.

TB and TiB (and their smaller counterparts, GB and GiB) represent different ways to measure digital storage. While both refer to data size, they use different counting systems. TB and GB are based on the decimal system (counting in tens), while TiB and GiB are based on the binary system (counting in twos), which is how computers naturally operate.

Because of this difference in counting systems, a TiB is slightly larger than a TB; the same holds true for GiB and GB. Although the difference might seem insignificant for smaller amounts of data, everything changes drastically when dealing with larger storage capacities.

That being said,

• 1 TiB (Tebibyte) equals approximately 1.09951 TB (Terabytes).
• 1 GiB (Gibibyte) equals approximately 1.07374 GB (Gigabytes).

Let’s dive in!

On-Demand

First things first, is BigQuery free? Well, it indeed offers certain capacities at no charge, but there’s a cap (more on that below). If you exceed it while no longer in a trial period, the payment is mandatory. 

Now, let’s get to on-demand BigQuery pricing. Those who decide to go with it pay for the exact amount of data processed by the queries, which offers flexibility for workloads with varying patterns. This model will be a great fit if you have unpredictable workloads or experience difficulty estimating resource consumption in advance. The good news is that the first 1 TiB comes free of charge every month.

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EMEA

LATAM

NA

Capacity Compute BigQuery Pricing

Alternatively, capacity-based pricing involves pre-purchasing a fixed amount of processing power, measured in slots (which essentially are virtual CPUs). With this model, you will have decent BigQuery price predictability and performance guarantees, making it ideal for workloads with consistent and high-volume query processing. It does, however, require careful capacity planning to avoid overspending on unused resources.

This BigQuery pricing model comes in three editions (in case you’d like to consider all of your options at this point, BigTable vs. BigQuery would make a good read!).

Standard

The Standard Edition is designed for development, testing, and ad-hoc analysis workloads. It utilizes a slot-hour pricing model with a minimum charge of one minute per slot. The compute resources are managed through an auto-scaling mechanism, automatically adjusting to workload demands.

This edition imposes limitations on capacity, allowing a maximum of 1,600 slots per reservation and 10 reservations per administrative project. The Standard Edition does not offer capacity commitment plans, making it suitable for unpredictable workloads but potentially leading to higher consistent processing costs. The service-level objective (SLO) for the Standard Edition delivers a 99.9% monthly uptime.

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NA

Enterprise

The Enterprise Edition is designed for production workloads requiring higher performance and advanced features. It employs a slot-hour pricing model similar to the Standard Edition but with a hybrid compute model combining auto-scaling with a guaranteed baseline. Unlike the Standard Edition, the Enterprise Edition imposes quotas on the number of reservations and limits the maximum number of reservations to 200 per admin project.

To encourage long-term commitments, the Enterprise Edition offers capacity commitment plans. Customers can choose between a one-year commitment for a 20% discount or a three-year commitment for a 40% discount. This edition provides a higher service-level objective (SLO) of 99.99%, ensuring greater reliability and uptime. On top of that, it introduces the ability to opt for multi-cloud analytics and ML capabilities, among others.

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NA

Enterprise Plus

The Enterprise Plus edition expands on the Enterprise edition with additional features such as compliance controls via Assured Workloads, access to managed disaster recovery, and more.

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NA

Storage

Google BigQuery pricing categorizes stored data into two primary types of storage: active and long-term. Data that has been modified within the past 90 days is considered active. This data type is readily accessible for querying and analysis but comes at a higher storage cost.

Conversely, data that remains unchanged for 90 consecutive days transitions to long-term storage. While still accessible, long-term storage might incur slightly longer query latencies. The benefit of long-term storage is that it significantly reduces BigQuery costs compared to active storage.

It’s important to note that the transition between the two is automatic, and the first 10 GiB each month comes free of charge.

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