BigQurey: Utilities And Advantages
Google's BigQuery comes with enterprise data warehouse for efficient data analysis, integration, visualization and reporting using standard SQL dialects and efficient tools at an unmatched price performance.
BigQuery is Google's enterprise data warehouse for efficient data analysis as it facilitates seamless data integration, transformation, analysis, visualisation and reporting with efficient tools from Google at an unmatched price-performance. Not a real-time system, but in case of OLAP it's unbeatable.
Utilities and Advantages:
Serverless data with high availability for efficient analysis even in the case of extreme failure modes.
Integrates exceptionally well with Google Storage by pushing CSV to Google Storage, and add it to BQ.
Seamless scaling to store and analyse petabytes of data without managing the infrastructure.
Flexible pricing models enabling pay as you use and store.
Data encryption and security.
Easy programmatic access and application integration by offering libraries in Java, Python, Node.js, C#, Go, Ruby, and PHP.
Supports standard SQL dialects which is ANSI:2011 compliant. Analyse all your data from one place. It can process data from Cloud Storage, Cloud Bigtable and also Cloud Spreadsheets in Google Drive.
Integration of ML to your data with Cloud ML Engine and TensorFlow.
Automated backup and data restore as it keeps a seven-day history of changes.
It provides integration with the Apache Big Data ecosystem, allowing existing Hadoop/Spark and Beam workloads to read or write data directly with the help of Cloud Dataproc and Cloud Dataflow.
It provides rich monitoring, logging, and alerting through Stackdriver Audit Logs.
According to a survey comparing BigQuery with other competitors,
BigQuery has been proved to be an awesome database platform, easy, simple and fun to use. Simplicity is one of the most important aspects of a product and it also ranks way ahead in case cost efficiency.