Exam Professional Cloud Architect topic 1 question 16 discussion

B. Google Cloud Bigtable

B, Bigtable due to the IoT like requirements

Google Cloud Bigtable is well-suited for handling high-throughput, low-latency workloads like clickstream data. It is optimized for analytics on time-series and event data at scale, and it supports high write rates, with the capacity to handle thousands of writes per second. This makes it ideal for storing large volumes of clickstream data with bursts, ensuring data is available for analysis by data science and user experience teams.

1. High throughput for clickstream data: Bigtable is a NoSQL database designed for high write throughput, making it ideal for handling the continuous stream of click data with bursts up to 8,500 clicks per second. 2. Scalability: Bigtable is highly scalable, allowing you to handle increasing data volumes as your website portfolio grows. 3. Low latency: Bigtable provides low latency data access, which is important for real-time analysis and reporting on clickstream data. 4. Integration with BigQuery: Bigtable integrates well with BigQuery, enabling your data science team to perform complex analysis and generate insights from the clickstream data.

Big table if it needs real time but here the need for analysis is not urgent => Google cloud storage.

The right answer is BigTable for a such large volume of data.

B. Google cloud Bigtable is most suitable as it is for analysis and streamed data.

Note: DataStore is now rename as FireStore.

B is correct

Bigtable is a high-perf NoSQL db service that handle large volumes of structured data with low latency

The Google Cloud Bigtable goes together with the BigQuery. The question itself gives away a bit.

For storing click-data that is streamed in at a rate of 6,000 clicks per minute, with bursts of up to 8,500 clicks per second, and that needs to be stored for future analysis by your data science and user experience teams, you should consider using a scalable, high-performance, and low-latency NoSQL database such as Google Cloud Bigtable, option B. Google Cloud Bigtable is a fully managed, high-performance NoSQL database service that is designed to handle large volumes of structured data with low latency. It is well-suited for storing high-velocity data streams and can scale to handle millions of reads and writes per second. Option A: Google Cloud SQL, option C: Google Cloud Storage, and option D: Google Cloud Datastore, would not be suitable for this use case, as they are not designed to handle high-velocity data streams at this scale.

B. Google Cloud Bigtable Google Cloud Bigtable is a scalable, high-performance NoSQL database that is well-suited for storing large amounts of data with low latency. It is designed for high-throughput workloads such as streaming data, and is able to handle bursts of up to millions of reads and writes per second. Given the high volume of click data that needs to be stored and the requirement for low latency, Google Cloud Bigtable would be a good choice for storing the data. It is able to handle the high rate of incoming data and provide fast access to the data for analysis by the data science and user experience teams. Google Cloud SQL is a fully-managed relational database service, and may not be the best choice for storing high-volume streaming data. Google Cloud Storage is an object storage service, and may not provide the necessary performance for storing and querying large amounts of data in real-time. Google Cloud Datastore is a NoSQL document database, and while it may be suitable for storing large amounts of data, it may not provide the necessary performance for handling high volumes of streaming data.

https://cloud.google.com/bigtable#section-9

B. Google Cloud Bigtable

Cloud Bigtable has all the features to fulfill the requirements mentioned in the question

D is right answer