The characteristic of BigQuery

The characteristic of BigQuery platform is a low-cost, multi-cloud, enterprise data warehouse, fully managed by Google. This tool assists the user in data management and analysis through the use of features such as embedded machine learning, geospatial analysis, and business-class intelligence.

BigQuery also has a distributed analytics engine that makes it easy to scale the system, allowing you to query Terabytes in seconds and Petabytes in minutes.

The characteristic of BigQuery

Among the characteristic elements of BigQuery are:

Serverless infrastructure

BigQuery’s architecture is characterized by not needing external servers, which allows the use of SQL queries to solve the organization’s biggest questions, without the need to manage the infrastructure. This implies that Google provisions its resources in the background , so that the client does not have to worry about updating, security management or infrastructure administration. All of this helps you focus your efforts on data and data analysis.

This means that BigQuery is a completely self-contained platform, so the user does not need to manage any infrastructure or have a database administrator .


The interfaces of this platform include the Google Cloud Console tool, as well as the BigQuery command line element , which allows users and developers to use client libraries with common programming such as Python , Java or JavaScript, among others. .

In addition, the interface of this tool is characterized by being based on spreadsheets . Users have the ability to use a large number of rows of data in these Google Sheets, even if they have no knowledge of SQL. This feature also allows the use of other elements that facilitate the user’s work, such as dynamic tables, formulas and graphs focused on the simple extraction of valuable information from macro data or big data .

Multi-cloud capacity

The BigQuery infrastructure supports the analysis of data from different clouds through the standard SQL language and platform interface. It has other multi-cloud capabilities that are responsible for offering the user a totally fluid data analysis experience.

Storage and high availability

This tool fulfills the function of storing data through a column-based format for analytical queries . This data is presented using tables, columns, and rows, and provides full support for database transaction semantics. This storage is automatically and transparently replicated in different locations, in order to provide a highly available service. This availability does not require additional configurations or the payment of extra costs.

Real-time analysis

Google BigQuery also provides real -time data analysis through the Application Development Interface API, focused on the platform’s high-speed streaming push . It functions as a highly analytics-powered database, immediately providing the user with the latest business data for analysis.

Business Intelligence

Another feature of this tool is that it is the foundation of modern artificial intelligence solutions in the cloud , because it allows users to carry out optimization tasks such as integration, analysis, transformation, visualization and reporting. of data through the use of different technological tools.

In addition, Google BigQuery makes it easy to use services like BI Engine , which helps streamline business intelligence workloads and provides query response times of up to less than a second, with high concurrency across business intelligence tools. more used.

Centralized administration

BigQuery is also characterized by a centralized management of data resources and protected processing with Identity and Access Management (IAM), which is the access model used in the Google Cloud Platform .

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