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Google BigQuery

Google BigQuery

Cloud Data WarehouseProduct· part of Googlecloud.google.com

Google BigQuery is Google's powerful cloud data warehouse that enables scalable analysis of large volumes of data, supporting queries written in GoogleSQL and including built-in machine learning capabilities.

Last updated Oct 13, 2026 by ATDb automated enrichment

Founded
2010
HQ
Mountain View, California, United States
Parent
Google
Connections
84

AI-drafted from public sources2 sources cited

At a glance

Employees
10001+
Revenue
Part of Google Cloud, which reported $43B+ in 2024 annual revenue
Stock
GOOGL
78integrations2competitors1corporate family
Data & AnalyticsAttribution & Analytics

About

Leading cloud data warehouse, widely adopted by marketers and data teams for large-scale ad performance analytics and cross-platform reporting

Google BigQuery is Google's powerful cloud data warehouse that enables scalable analysis of large volumes of data, supporting queries written in GoogleSQL and including built-in machine learning capabilities. For marketers and advertisers who need a unified view of performance across platforms such as Google Ads, Facebook Ads, and Google Analytics, BigQuery allows all raw data to be brought together in one place and then connected to external visualization tools like Power BI, Tableau, or Looker to produce final reports. A key advantage for the advertising industry is BigQuery's ability to configure data collection from Google services such as Google Ads, GA4, and Search Console in just a few clicks. BigQuery enables structured and scalable access to ad data, allowing users to generate consistent, actionable reports across campaigns and use those insights to refine ad targeting, adjust bid strategies, and optimize budgets for better ROI. BigQuery offers transparent, usage-based pricing, so customers pay only for the resources they use. Source 1: proanalytics.academy — What is Google BigQuery: Benefits for Marketing and ... Source 2: windsor.ai — Connect Google Ads to BigQuery

Business model

Usage-based Cloud Service (PaaS)

Target market

Enterprise

What they offer

  • BigQuery Studio

    Unified analytics workspace for data exploration, SQL querying, and notebook-based analysis

  • BigQuery ML

    Built-in machine learning capabilities allowing users to create and run ML models using SQL directly within BigQuery

  • BigQuery Omni

    Multi-cloud analytics solution enabling queries across data stored in AWS and Azure alongside Google Cloud

  • BigQuery BI Engine

    In-memory analysis service for fast, interactive querying and integration with Looker Studio and other BI tools

  • BigQuery Data Transfer Service

    Automated data ingestion from Google Ads, GA4, YouTube, Search Console, and third-party sources into BigQuery

  • BigQuery Streaming

    Real-time data ingestion and querying for up-to-the-minute analytics on ad performance and user behavior

Key features

Serverless, fully managed cloud data warehouseGoogleSQL support for familiar queryingBuilt-in machine learning via BigQuery MLNative integrations with Google Ads, GA4, and Search ConsoleScalable to petabytes of dataUsage-based, pay-as-you-go pricingMulti-cloud analytics with BigQuery OmniIntegration with Looker, Tableau, Power BI, and other BI toolsReal-time streaming ingestionRow- and column-level security controls

Use cases

Unified cross-platform ad performance reporting (Google Ads, Facebook Ads, GA4)Campaign ROI analysis and budget optimizationAd targeting refinement using audience and behavioral dataBid strategy optimization through historical performance analysisMarketing attribution modelingCustomer segmentation for advertising audiencesReal-time dashboards via Looker Studio or TableauPredictive analytics for media spend forecasting

Customer segments

Enterprise marketing and analytics teamsDigital advertisers and media agenciesData engineers and BI developersE-commerce companies managing large ad datasetsPublishers and media companiesMid-market companies scaling their data infrastructure

Tech & specs

Technology stack

GoogleSQLDremel query engineColossus distributed file systemApache Beam (Dataflow integration)TensorFlow / Vertex AI integrationREST and gRPC APIsdbt compatibilityLooker / Looker Studio

Security & compliance

SOC 1SOC 2SOC 3ISO 27001GDPRCCPAHIPAAFedRAMP

Deployment

Cloud

API

Yes

Explore further

3 views
On the AtlasAttribution & AnalyticsOn the Mapby country + regionOn the GraphNetwork around Google BigQuery