Google BigQuery Integration
BigQuery is a highly scalable and robust data warehouse offering by Google. Its serverless architecture is aligned to the modern data application requirements and allows you to make quick, data-driven decisions through its state-of-the-art analytics capabilities. As a modern data warehouse solution, BigQuery is built to handle large data workloads with ease. It is a highly cost-effective solution, giving you all the resources you need to transform your data into valuable business insights at a reasonable price.
What You Can Do with Google BigQuery
- Save precious time and effort with a fully managed data warehouse that is easy to set up and manage
- Perform machine learning, predictive analytics, and rich data visualization
- Integrate your data with other tools such as Google Analytics
- Enable freeloading and exporting data with reasonable charges for data storage, data streaming and real time querying
Setting up a BigQuery data warehouse on your own can be quite exhausting and time-consuming. You have to build and maintain the data warehouse from scratch, in addition to defining the schema that determines how the data from the sources gets stored in the warehouse.
By simply connecting BigQuery as a destination in RudderStack, you can get started in no time at all.
Collect, Store, and Analyze Your Event Data with Lightning-fast Speed Using RudderStack and Google BigQuery
RudderStack supports sending your event data from a variety of sources to Google BigQuery. Once you add BigQuery as a destination in RudderStack, all your event data is stored into BigQuery buckets periodically. With RudderStack, you don’t have to worry about defining a warehouse schema either – it will take care of everything.
By Integrating BigQuery Support with RudderStack, You Can:
- Directly send your event data from a variety of sources, including web and mobile
- Load data into BigQuery without having to define a warehouse schema
- Get the data already transformed and ready for analytics
- Focus solely getting relevant business insights out of your data rather worrying about storing and retrieving it
What is BigQuery used for?
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.
Is BigQuery a database?
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.
Is BigQuery relational?
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.
What is BigQuery based on?
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.
Google Cloud Storage