Introduction to BigQuery editions

This document provides an introduction to BigQuery editions and the features associated with them.

Overview

BigQuery provides three editions (Standard, Enterprise, and Enterprise Plus) to support different types of workloads. These editions provide an alternative to existing reservation models, such as flat-rate or on-demand models. You can choose to use editions, flat-rate reservations, or on-demand models at the same time.

Each edition provides a set of capabilities at a different price point to match the requirements of different types of customers. You can create a reservation or a capacity commitment associated with an edition. Capacity commitments are not required to purchase slots, but can save on costs. For more information about slots autoscaling, see Introduction to slots autoscaling. As BigQuery editions is a property of compute power, not storage, you can query datasets regardless of how they are stored as long as you are not using a non-matching edition specific capability.

Editions features

The following table lists the features available in each edition. Features outside of your edition are blocked or lack functionality.

	Standard	Enterprise	Enterprise Plus	Non-edition offerings
Pricing model	Slot-hours (1 minute minimum)	Slot-hours (1 minute minimum)	Slot-hours (1 minute minimum)	Flat-rate slots (flex, monthly, annual) / Pay per query with free tier
Compute model	Autoscaling	Autoscaling + Baseline	Autoscaling + Baseline	On-demand or fixed-slot reservation
Maximum reservation size	1,600 slots	Quota	Quota	Quota
Maximum reservations per administration project	5
Committment plans		1-year commitment at 20% discount or 3-year commitment at 40% discount	1-year commitment at 20% discount or 3-year commitment at 40% discount	Monthly and annual commitment discounts
Monthly Service Level Objective (SLO)	>=99.9%	>=99.99%	>=99.99%	>=99.99%
Compliance controls			Compliance controls through Assured Workloads	Compliance controls through Assured Workloads
VPC Service Controls		VPC Service Controls Support	VPC Service Controls Support	VPC Service Controls Support
Data governance		Column-level access control Row-level security Dynamic data masking	Column-level access control Row-level security Dynamic data masking	Column-level access control Row-level security Dynamic data masking
Storage encryption	Google-managed keys	Google-managed keys	Customer-managed keys (CMEK) Google-managed keys	Customer-managed keys (CMEK) Google-managed keys
Business Intelligence acceleration		Query acceleration through BI Engine	Query acceleration through BI Engine	Query acceleration through BI Engine
Materialized views	Query existing materialized views directly	Create materialized views Automatic refresh of materialized views Manual refresh of materialized views Direct query of materialized views Smart tuning	Create materialized views Automatic refresh of materialized views Manual refresh of materialized views Direct query of materialized views Smart tuning	Create materialized views Automatic refresh of materialized views Manual refresh of materialized views Direct query of materialized views Smart tuning
Search	Access to the SEARCH function without access to search indexes	Query acceleration with search indexes	Query acceleration with search indexes	Query acceleration with search indexes
Unstructured data	Query object tables	Object tables with ML inference	Object tables with ML inference	Query object tables
Integrated machine learning		BigQuery ML	BigQuery ML	BigQuery ML
Workload management	Users cannot set the maximum concurrency target	Advanced workload management (idle capacity sharing, target concurrency)	Advanced workload management (idle capacity sharing, target concurrency)	Flat-rate users have access to idle capacity sharing and target concurrency On-demand users do not have access to Advanced workload management
Supported assignment types	QUERY, PIPELINE	QUERY, PIPELINE, ML_EXTERNAL, BACKGROUND	QUERY, PIPELINE, ML_EXTERNAL, BACKGROUND	QUERY, PIPELINE, ML_EXTERNAL, BACKGROUND
Multi-cloud analytics		BigQuery Omni support		BigQuery Omni support

Edition tiers should not be used to restrict access to specific features, as the features assigned to each edition could change over time. For example, do not assign projects to Standard edition reservations just to disable BigQuery ML.

Storage encryption support

BigQuery automatically encrypts all data at rest. By default, Google manages the key encryption keys used to protect your data. You can also use customer-managed encryption keys (CMEK) in Enterprise Plus edition.

Note: CMEK offerings that were accessible on or before July 5, 2023 will continue to be accessible in Enterprise edition to customers who purchased BigQuery slots before this date.

Assured Workloads support

BigQuery Enterprise Plus edition supports Assured Workloads platform controls for regulatory compliance regimes, including FedRAMP, CJIS, IL4, and ITAR.

Assured Workloads offerings that were accessible on or before July 5, 2023 will continue to be accessible in Enterprise edition to customers who purchased BigQuery slots before this date.

Editions FAQs

How is BigQuery pricing changing?

We are changing BigQuery's analytics models and pricing. The changes can give you new ways to optimize your spending based on workload type and size.

• We are introducing a new consumption and reservation model, BigQuery editions, that offers a tiered pricing structure with curated feature sets for different workload needs. All editions are enabled with our new autoscaler functionality that offers fully elastic, dynamic scaling of BigQuery compute resources without pre-provisioning capacity.
• We are also increasing the price of BigQuery on-demand analysis (pay-per-query pricing) to reflect the improvements in our serverless functionality and performance.

How do I know if I am impacted by these pricing changes?

The price changes are relevant:

• All customers with existing BigQuery reservation spend (flat-rate or flex slots)
• All customers with existing BigQuery on-demand analysis spend

When do the price changes take effect?

The Mandatory Service Announcement (MSA) notifying customers about price changes for on-demand analysis and the upcoming end of sale of flat-rate and flex slots was sent to impacted partners and customers on March 30, 2023, providing more than 90 days' notice before the changes take effect on July 5, 2023.

When and how am I notified about these changes?

Customers were notified by a Mandatory Service Announcement (MSA) on March 30, 2023. If you haven't received an MSA, refer to the blog post.

Are these price changes reflected globally?

The changes will apply globally. For any pricing adjustments, local currency list prices will be adjusted to USD prices to avoid currency arbitrage.

What can I do to prepare for these change?

You do not need to do anything if you exclusively use the on-demand analysis model.

If you have existing flat rate and/or flex slot reservations, your capacity will be automatically converted to BigQuery editions. New pricing takes effect starting on July 5, 2023. At any time before or after the conversion, you can choose to modify your capacity configuration to use optional 1-year or 3-year capacity commitments (available in Enterprise and Enterprise Plus editions) for greater cost savings.

When will the new prices take effect?

Commercial migration of flat-rate and flex-slot pricing into editions pricing happens starting on July 5, 2023. Monthly flat rate and flex slots will be converted to new prices on July 5, and annual flat rate pricing converts to editions pricing at time of renewal.

Why is Google making these changes?

Over the past several years, Google Cloud has made significant investments in BigQuery features and performance that have benefited our customers. Many of the changes have added capabilities for enterprise data warehouses or improved performance. As we continue to add these capabilities, we are also making adjustments to BigQuery's consumption model and pricing to align more closely with how customers want to purchase analytics capacity. These changes provide customers more flexibility to optimize their data workloads for price-performance while allowing them to pay only for what they use, unlike market alternatives with upfront provisioning and unpredictable costs. For more information, see the latest BigQuery cost optimization guide to learn more.

What is Google Cloud's pricing philosophy?

Google Cloud offers innovative solutions to transform businesses, priced in a customer-focused and market-consistent way. Every organization is on its own unique cloud journey. To help, we're developing ways for customers to consume and pay for Google Cloud services. We're doing this by removing barriers to entry, aligning cost to consumption and providing contractual and product flexibility.

With our pay-as-you-go pricing structure, you only pay for the services you use. BigQuery also can save you money over other providers, thanks to dynamic autoscaling and the ability to pre-commit for compute resources at discounted rates. For example, if you select Enterprise or Enterprise Plus Editions for your workloads with a 1-year or 3-year commitment, you automatically receive a discount from list prices, without contracting changes. These updates are consistent with our overall pricing philosophy.

What should I do next?

If you are using the on-demand analysis model, no action is needed. If you are using the flat-rate model, you can work with your Google account teams and partners to plan workload migrations to the new editions model. To learn more about BigQuery editions, you can register to watch the BigQuery roadmap session from April 5, 2023.

Pricing

For information about BigQuery editions pricing, see BigQuery pricing.

Quotas

Slots from all editions are subject to the same quota. Your quota is not fulfilled on a per-edition basis. For information about quotas, see Quotas and limits.

What's next

• For more information on slots autoscaling, see Introduction to slots autoscaling.
• For more information on reservations, see Introduction to Reservations.