Google BigQuery is a GCP data warehouse that enables developers to send data from their Data Warehouse.

Difficulty can vary based on your data structure, data cleanliness and required destinations. Many users choose to simplify implementation by sending warehouse data through secure GCP data warehouse integration tools like RudderStack.

Pricing for Google BigQuery can vary depending on your use case and data volume. RudderStack offers transparent, volume-based event pricing. See RudderStack's pricing.

Google BigQuery is a web service offering from Google used for handling and analyzing Big Data. As a part of the Google Cloud Platform, BigQuery allows you to manage large amounts of data and perform real time analysis using SQL-like queries. BigQuery follows the principle of NoOps (No Operations), a concept which implies there is no need for a dedicated team to manage the tool.

Google BigQuery is a managed data warehouse. This means that you can access the data stored in BigQuery by using SQL queries. BigQuery self-manages the storage, encryption, scaling and performance management aspects of your data.

BigQuery is a REST-based web service. It allows you to run complex analytical queries for large amounts of data using SQL. BigQuery is not a substitute for a traditional relational database. It is primarily used for running analytical queries, and not for simple CRUD operations or queries.

BigQuery is built using the Google Dremel paper, which is also an inspiration for other popular tools such as Apache Drill, Apache Impala, and Dremio. Dremel is Google’s distributed system used for interactive querying of large datasets. It is capable of running queries over trillions of rows in seconds.