BigQuery

BigQuery is a fully managed, serverless data warehouse and analytics platform provided by Google Cloud. It enables super-fast SQL queries using the processing power of Google's infrastructure, allowing users to analyze massive datasets in seconds. It supports both batch and real-time data ingestion, with built-in machine learning capabilities and integration with other Google Cloud services.

Also known as: Google BigQuery, Big Query, BQ, GCP BigQuery, Google Cloud BigQuery

🧊Why learn BigQuery?

Developers should learn BigQuery when working with large-scale data analytics, data warehousing, or business intelligence applications, especially in cloud-native environments. It is ideal for scenarios requiring petabyte-scale querying, real-time analytics, or integration with Google's ecosystem, such as marketing analytics, IoT data processing, or financial reporting. Its serverless architecture eliminates infrastructure management, making it cost-effective for variable workloads.

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Compare BigQuery

BigQuery vs Amazon Redshift→BigQuery vs Snowflake→BigQuery vs Microsoft Azure Synapse→

Learning Resources

BigQuery Documentation

BigQuery Tutorial for Beginners

BigQuery in 5 Minutes

BigQuery: The Definitive Guide

Related Tools

Google Cloud Platform Sql Data Warehousing Apache Beam Looker Studio

Alternatives to BigQuery

Amazon Redshift Snowflake Microsoft Azure Synapse

Other Cloud SQL

Always On Availability Groups

Always On Availability Groups is a high-availability and disaster recovery solution in Microsoft SQL Server that provides database-level failover for groups of databases. It allows multiple copies of a set of databases (availability replicas) to be maintained across different servers, ensuring data redundancy and automatic failover in case of primary server failure. This feature supports both synchronous and asynchronous data replication modes to balance performance and data protection needs.

Amazon Aurora is a fully managed, MySQL and PostgreSQL-compatible relational database service built for the cloud. It combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases, offering up to five times the throughput of standard MySQL and three times that of PostgreSQL. Aurora automatically handles tasks like hardware provisioning, database setup, patching, backups, and replication, while providing high durability and availability through distributed, fault-tolerant, self-healing storage.

Amazon Aurora Provisioned

Amazon Aurora Provisioned is a fully managed relational database service from AWS that offers high performance, scalability, and availability with MySQL and PostgreSQL compatibility. It uses a distributed, fault-tolerant storage system that automatically scales up to 128 TB per database instance, providing fast read replicas and continuous backup to Amazon S3. This provisioned model requires users to pre-allocate and pay for database instance capacity, making it suitable for predictable workloads.

Amazon Aurora Serverless

Amazon Aurora Serverless is an on-demand, auto-scaling configuration for Amazon Aurora, a MySQL and PostgreSQL-compatible relational database built for the cloud. It automatically starts up, shuts down, and scales capacity up or down based on application demand, eliminating the need to manage database instances. This serverless model is designed for applications with intermittent, unpredictable, or variable workloads.

Amazon Aurora Serverless

Amazon Aurora Serverless is an on-demand, auto-scaling configuration for Amazon Aurora, a MySQL and PostgreSQL-compatible relational database built for the cloud. It automatically starts up, shuts down, and scales capacity up or down based on application demand, eliminating the need to manage database instances. This serverless model is designed for applications with intermittent, unpredictable, or variable workloads.

Amazon DynamoDB

Amazon DynamoDB is a fully managed NoSQL database service provided by Amazon Web Services (AWS) that offers fast and predictable performance with seamless scalability. It supports key-value and document data models, automatically replicates data across multiple Availability Zones for high availability and durability, and provides built-in security, backup, and in-memory caching capabilities.