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BigQuery - Data Warehouse

BigQuery is Google's serverless, highly scalable data warehouse with built-in machine learning and real-time analytics.

Data Analytics
Pricing Model Pay-per-query or flat-rate monthly
Availability Multi-region including EU
Data Sovereignty EU multi-region available
Reliability 99.99% monthly uptime SLA

What is BigQuery?

BigQuery is Google Cloud’s fully managed, serverless data warehouse for analytics at any scale. The service separates storage and compute, enabling independent scaling of each. You can analyze petabytes of data in seconds using standard SQL without managing any infrastructure.

Core Features

  • Serverless Architecture: No cluster management, automatic scaling, pay only for what you use
  • Petabyte Scale: Analyze massive datasets in seconds with distributed query execution
  • BigQuery ML: Train and deploy machine learning models using SQL directly in BigQuery
  • Real-time Streaming: Ingest and analyze streaming data in real-time
  • Geospatial Analysis: Native support for geographic data types and functions

Typical Use Cases

Business Intelligence

Connect BigQuery to Looker, Tableau or other BI tools for interactive dashboards. BI Engine provides sub-second query responses for demanding visualizations.

Log and Event Analytics

Centralize application logs and events in BigQuery for analysis. Query terabytes of log data in seconds to identify issues and trends.

Data Science and ML

Data scientists query data directly in BigQuery and train models using BigQuery ML. No data movement required between storage and ML platforms.

Benefits

  • Sub-second queries on petabyte-scale data
  • No infrastructure management or capacity planning
  • Built-in machine learning with SQL
  • Seamless integration with the entire GCP data stack

Integration with innFactory

As a Google Cloud Partner, innFactory supports you with BigQuery: data warehouse architecture, migration from on-premises or other cloud DWH, query optimization and cost management. We help build modern data platforms.

Available Tiers & Options

Editions (Standard/Enterprise)

Strengths
  • Autoscaling with reserved capacity
  • Advanced security features
  • Predictable pricing
Considerations
  • Minimum commitment required

Typical Use Cases

Business Intelligence
Real-time Analytics
Log Analysis
Data Science
Geospatial Analysis

Technical Specifications

Max table size Petabyte scale
Ml integration BigQuery ML for in-database machine learning
Query engine Dremel-based distributed query engine
SQL dialect Standard SQL with extensions
Storage Columnar storage with automatic optimization

Frequently Asked Questions

How is BigQuery different from traditional databases?

BigQuery is optimized for analytical queries across petabytes of data using a serverless architecture. Traditional databases are designed for transactional workloads with row-based storage.

Can I query data without loading it into BigQuery?

Yes, BigQuery supports external tables that query data directly from Cloud Storage, Google Drive, or Cloud Bigtable without importing.

What is BigQuery ML?

BigQuery ML enables creating and executing machine learning models using standard SQL queries, without moving data or learning Python/TensorFlow.

How does BigQuery pricing work?

On-demand pricing charges per TB scanned. Flat-rate and Editions pricing provides dedicated capacity for predictable costs. Storage is billed separately at low rates.

Google Cloud Partner

innFactory is a certified Google Cloud Partner. We provide expert consulting, implementation, and managed services.

Google Cloud Partner

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