Google BigQuery

What differentiates Google BigQuery from other similar products?

Google BigQuery provides many functionalities to detect query data scan and query execution time before execution , allowing you to set policies to prevent poorly written queries from getting executed. It is very east to setup and performant

What is your favorite aspect of this product?

The east of use with google bigquery is very high, it also allows to connect google sheet to google big query via Connected Sheets feature

What do you dislike most about this product?

the pricing is not very competitive, it has compute and storage cost , because of the storage cost component you are charged for data which is loaded in big query

What recommendations would you give to someone considering this product?

For any team working in google cloud , using google bigquery is a simple solution to setup a data warehouse which is performant when you have a smaller team and want to get results faster

What differentiates Google BigQuery from other similar products?

Google BigQuery sets itself apart from other similar products through its exceptional speed and scalability in processing large-scale datasets. The platform's serverless architecture eliminates the need for infrastructure management, enabling users to focus solely on querying and analyzing data. Its unique billing model, based on on-demand pricing, ensures cost-effectiveness by charging only for the resources used during queries, making it a flexible and cost-efficient solution. Additionally, seamless integration with other Google Cloud services and robust support for real-time data

What is your favorite aspect of this product?

As a data engineer, what truly impresses me about Google BigQuery is its lightning-fast processing speed and hassle-free scalability. The way it effortlessly handles large datasets, allowing me to focus on data engineering tasks without worrying about infrastructure management, is a game-changer. The serverless architecture and pay-as-you-go pricing model make it not only efficient but also cost-effective. Moreover, the seamless integration with other Google Cloud services adds an extra layer of convenience to my workflow. Google BigQuery, with its speed, scalability, and ecosystem integration, has become my go-to tool for efficient pipeline

What do you dislike most about this product?

While Google BigQuery excels in many aspects, one area that can be challenging is the cost, especially for large and complex queries. The on-demand pricing model, while flexible, can lead to unpredictability in expenses, and users need to be mindful of optimizing queries to manage costs effectively. Additionally, there might be occasional limitations in terms of advanced data preparation features within the platform, requiring users to perform some tasks outside of BigQuery.

What recommendations would you give to someone considering this product?

For those considering Google BigQuery, I would recommend carefully assessing your data engineering needs and ensuring compatibility with the platform's strengths in speed and scalability. Take the time to understand the on-demand pricing model and optimize your queries to manage costs effectively. Leverage the seamless integration with other Google Cloud services to maximize the platform's potential within your ecosystem. Additionally, stay updated on new features and enhancements, as Google Cloud regularly introduces improvements to the platform.

What differentiates Google BigQuery from other similar products?

Ease of use. As it is very obvious with all the google products, it is very easy to use and works really well with other corresponding tools.

What is your favorite aspect of this product?

It has a very casual UI so that makes it easy to use. It integrates well other tools like BI tools and ETL tools.

What do you dislike most about this product?

Nothing really there to dislike about Bigquery. May be they can make the data warehouse a little fast.

What recommendations would you give to someone considering this product?

If you don't have a huge data then this is the answer. Look no further away, If you have a huge data and you repeatedly process hundreds of millions of rows, then you still may consider Bigquery. Only difference is that in the first case Bigquery is the obvious winner.