For this question, refer to the Mountkirk Games case study. You need to analyze and define the technical architecture for the database workloads for your company, Mountkirk Games. Considering the business and technical requirements, what should you do?
Considering the diverse requirements of the database workloads for Mountkirk Games, it is essential to use different services optimized for specific tasks. Cloud Bigtable is ideal for time series data due to its ability to handle high throughput with low latency, which is crucial for real-time data analysis. Cloud Spanner is designed for transactional data with its strong consistency and horizontal scalability, making it suitable for managing user profiles and game state. BigQuery is tailored for handling large-scale data analysis and historical data queries, providing fast SQL-like querying capabilities. Therefore, using Cloud Bigtable for time series data, Cloud Spanner for transactional data, and BigQuery for historical data queries offers an optimal solution that aligns with the business and technical requirements.
For the people who say it's C in Linux Academy, did you see the Technical requirements there? The old Technical Requirements have the line "Connect to a managed NoSQL database service" but in the Technical Requirements in Google official site and in this question the line is replaced if the following 2 lines "Connect to a transactional database service to manage user profiles and game state Store game activity in a timeseries database service for future analysis". And for them definitely D is the answer!
Correct Answer D Use Cloud Bigtable for time series data, use Cloud Spanner for transactional data, and use BigQuery for historical data queries. Storing time-series data in Cloud Bigtable is a natural fit, Cloud Spanner scales horizontally and serves data with low latency while maintaining transactional consistency and industry-leading 99.999% (five 9s) availability - 10x less downtime than four nines (<5 minutes per year). Cloud Spanner helps future-proof your database backend. After you load your data into BigQuery, you can query the data in your tables. BigQuery supports two types of queries: Interactive queries, Batch queries
I agree with above explanation and choice
vote D
D is right
I think it should be C. I can't justify using Spanner for transactional data. BigTable supports single-row transactions and can easily handle transactional and time series data at lower cost.
Vote D
D is the correct answer
D is the Answer
D Correct Answer D
C cannot be the answer
C is worong.Bigtable is NOSQL.Bigtable cant be alternative for MySQL. I think D is correct. Biquery most fit historical data queries.
DDDDD it is
D - GCP's classics best practice for tests
ok for D
D. Use Cloud Bigtable for time series data, use Cloud Spanner for transactional data, and use BigQuery for historical data queries. Based on the technical requirements provided, the best approach for analyzing and defining the technical architecture for the database workloads for Mountkirk Games would be to use Cloud Bigtable for time series data, Cloud Spanner for transactional data, and BigQuery for historical data queries.
Thought it's C then I reviewed the requirements there is transactional database for user profiles
DDDDDDDDDD