BigQuery

1. Overview

  • Delivers big data analysis and interactive data query.
  • Google's NoSQL, big data service.
  • Does not support multi-row transactions.
  • Ideal for storing a large amount of structured objects.
  • Supports ad hoc SQL queries on large datasets.
  • Supports SQL queries of large datasets with a pay-as-you-go model.
  • Fully manage petabyte scale, low cost analytics data warehouse.
  • Enables users to focus on analyzing data to find meaningful insights.
  • Suitable for interactive querying in an online analytical processing system with petabytes of scale.
  • BigQuery is used by all types of organizations from startups to Fortune 500 companies. 
  • Smaller organizations like Big Query's free monthly quotas, and larger organizations like its seamless scale.BigQuery users can run super fast SQL queries against terabytes of data in seconds.
  • BigQuery users can easily read and write data using Cloud Dataflow, Hadoop and Spark.
  • Data can be easily loaded into BigQuery from cloud storage.
  • Google's infrastructure is global and so is BigQuery.
  • BigQuery enables users to specify the region where their data will be kept.
  • BigQuery enables users to pay for data storage separately from queries.
  • BigQuery users pay for queries only when they are running.
  • BigQuery users can share data sets with users in other projects.
  • The user of the dataset is responsible for the cost of their own queries.
  • Long term storage pricing is automatically applied to data residing in BigQuery.
  • When the age of data reaches 90 days in BigQuery, Google will automatically drop the price of storage.
  • With BigQuery, there is no infrastructure to manage.
  • Storage costs and usage can be controlled and optimized by setting the default table exploration for newly created tables in a dataset.
  • Where expiration period property is set after a dataset is created, only new tables are deleted after the expiration period.
  • Where expiration period property is set when data-set is created, any table created in the dataset is deleted after the expiration period.
  • BigQuery IM roles can be used to ensure users are provided with only the permissions that align with their job function.
  • It is recommended to separate who is allowed to create and manage datasets from those who can query the datasets and process the data.
  • The principle of least privilege should be followed when providing access to sensitive data.
  • BigQuery authorized view can be used to limit users to see only a subset of the data.