Is Google Big Query the future of Big data analytics? Here is an evaluation?

https://medium.com/@Countants/is-google-bigquery-the-future-of-big-data-analytics-here-is-an-evaluation-7a639a6b3459
The article is saying that Google’s Big Query is an enterprise-grade cloud-native data warehouse. Big Query has evolved into a more economical and fully-managed data warehouse which can run blazing fast interactive and ad-hoc queries on datasets of petabyte-scale. In addition, Big Query now integrates with a variety of Google Cloud Platform services and third-party tools which makes it more useful. Nowadays, google uses the data from its Web index to initially match queries with potentially useful results. Besides, it makes our life more convenient, for we can search many things on the internet and the Google’s fully managed, serverless approach automatically takes care of performance, scalability, and availability requirements for your data analysis. With no infrastructure to manage, we can easily leverage products like Big Query to analyze gigabytes to petabytes of data in minutes, not months. Moreover, stream analytics from Google Cloud lets you accelerate the pace at which you serve customers, interpret the market, and run your business—without changing your existing team or straining your budget. Google’s unified data analytics platform provides easy access to stream and batch processing, and Apache Beam provides pipeline portability for hybrid or multi-cloud environments. To sum up, I think that Big Query is designed to query structured and semi-structured data using standard SQL. It is highly optimized for query performance and provides extremely high cost effectiveness. Big Query is a cloud-based fully-managed service which means there is no operational overhead. It is more suitable for interactive queries and OLAP/BI use cases. Google’s cloud infrastructure technologies such as Borg, Colossus, and Jupiter are key differentiator why Big Query service outshines some of its counterparts.

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