A simple answer would be ... it depends on what you want to do with your data.
Hadoop is used for massive data storage and batch processing of this data. It is very mature, popular, and you have many libraries that support this technology. But if you want to do real-time analysis, requests for your hadoop data are not suitable for it.
A large Google request was designed specifically to solve this problem. You can do real-time processing of your data with a large google request.
You can use Big Query instead of Hadoop, or you can also use a large query with Hadoop to query the datasets created by MapReduce jobs.
Thus, it completely depends on how you want to process your data. If a batch processing model is required and sufficient, you can use Hadoop, and if you want to process in real time, you need to choose Google.
Edit: You can also explore other technologies that you can use with Hadoop, such as Spark , Storm , Hive , etc. (and select depending on your use case)
Some useful links for further research:
1: gavinbadcock blog
2: cloudacademy blog