You have been asked to select the storage system for the click-data of your company's large portfolio of websites. This data is streamed in from a custom website analytics package at a typical rate of 6,000 clicks per minute. With bursts of up to 8,500 clicks per second. It must have been stored for future analysis by your data science and user experience teams.
Which storage infrastructure should you choose?
For storing high-velocity click-data that streams at a typical rate of 6,000 clicks per minute with bursts of up to 8,500 clicks per second, a storage infrastructure that can handle large volumes of structured data with low latency is essential. Google Cloud Bigtable is a scalable, high-performance NoSQL database specifically designed for such high-throughput workloads. It provides low-latency read/write access, which is necessary for both real-time and future analysis tasks by data science and user experience teams. In contrast, Google Cloud SQL is more suitable for relational database needs, Google Cloud Storage is best for storing large binary objects like images or videos, and Google Cloud Datastore, although a NoSQL database, is tailored more towards semi-structured data and would not handle the high volume of streaming data as efficiently as Bigtable.
B. Google Cloud Bigtable
B, Bigtable due to the IoT like requirements
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.
Bigtable for a high volume of writes. 8500 clicks per sec
Bigtable is a high-perf NoSQL db service that handle large volumes of structured data with low latency
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.
B. Google Cloud Bigtable
D is right answer
Cloud Bigtable has all the features to fulfill the requirements mentioned in the question
B. Google Cloud Bigtable
https://cloud.google.com/bigtable#section-9
The Google Cloud Bigtable goes together with the BigQuery. The question itself gives away a bit.
B is correct
Note: DataStore is now rename as FireStore.
B. Google cloud Bigtable is most suitable as it is for analysis and streamed data.
The right answer is BigTable for a such large volume of data.
Big table if it needs real time but here the need for analysis is not urgent => Google cloud storage.