Exam Professional Cloud Architect topic 1 question 20 discussion

C. Google Cloud Bigtable

1. High Write Throughput: Bigtable excels at handling high-volume write operations, which is crucial for your application receiving data from 50,000 sensors sending 10 readings per second. 2. Low Latency: Bigtable offers very low latency for read operations, essential for real-time charting and data visualization. 3. Time-Series Data: Bigtable is well-suited for storing and querying time-series data, like your weather sensor readings with timestamps. 4. Scalability: Bigtable can handle massive amounts of data and scale seamlessly as your application grows.

Bigtable - NoSQL, high-throughput, low-latency, making it suitable for storing time-series data from sensors

BigTable is NoSQL for IoT

C is correct

To optimize the performance of an accurate, real-time, weather-charting application that receives data from 50,000 sensors sending 10 readings per second, it would be most appropriate to store the data in a distributed, horizontally scalable, NoSQL database such as Google Cloud Bigtable Other options, such as Google BigQuery, Google Cloud SQL, and Google Cloud Storage, may not be as well-suited for handling high volumes of real-time data and may not provide the same level of performance and scalability as Google Cloud Bigtable.

C. Bigtable, IoT data.

C Bigtable

C bigtable right answer

real-time, IoT, time series and huge writes are some of the keywords to look after for Bigtable

C. Google Cloud Bigtable

C big table for IOT data

Google Cloud Bigtable

Keyword - Timestamp - Big table

Go for c

C. Google Cloud Bigtable is the Best Practice option

Ans c - when ever thier is input from IOT devices across and time series data which is huge go for big table in gcp