Exam AZ-305 topic 2 question 20 discussion

Cleared the exam on 01/05/23 with 871 / 1000. Chose CD. There is a similar question on ET where the option was SQL DB API

A. Azure Table Storage -> Throughput: scalability limit of 20,000 operations/s. -> Not enough for this question B. Azure Event Grid -> It is only a broker, not a storage solution Therefore, C and D are right Refs: https://learn.microsoft.com/en-us/azure/cosmos-db/table/ https://learn.microsoft.com/en-us/azure/event-grid/overview

C & D are correct

appeared in Exam 01/2024

The Time Series Insights (TSI) service will no longer be supported after March 2025. Consider migrating existing TSI environments to alternative solutions (such as Azure Data Explorer) as soon as possible. Azure Data Explorer is a fast, fully managed data analytics service for real-time and time-series analysis on large volumes of data streams from business activities, human operations, applications, websites, Internet of Things (IoT) devices, and other sources. https://learn.microsoft.com/en-us/azure/time-series-insights/migration-to-adx

Same as Question #9

C. Azure Cosmos DB for NoSQL D. Azure Time Series Insights Both Azure Cosmos DB and Azure Time Series Insights are suitable services for storing and querying the data in this scenario. C. Azure Cosmos DB for NoSQL is a globally distributed, multi-model database service that can handle large amounts of data with low-latency and high throughput. Its support for various consistency levels and partitioning strategies makes it suitable for handling IoT data at scale. D. Azure Time Series Insights is a fully managed, real-time analytics service specifically designed for time-series data generated by IoT devices. It provides storage, visualization, and advanced querying capabilities for time-series data, making it an ideal choice for handling data from a large number of IoT devices and visualizing it in near real-time.

C. Azure Cosmos DB for NoSQL D. Azure Time Series Insights Both Azure Cosmos DB and Azure Time Series Insights are suitable services for storing and querying the data in this scenario. C. Azure Cosmos DB for NoSQL is a globally distributed, multi-model database service that can handle large amounts of data with low-latency and high throughput. Its support for various consistency levels and partitioning strategies makes it suitable for handling IoT data at scale. D. Azure Time Series Insights is a fully managed, real-time analytics service specifically designed for time-series data generated by IoT devices. It provides storage, visualization, and advanced querying capabilities for time-series data, making it an ideal choice for handling data from a large number of IoT devices and visualizing it in near real-time.

CD is the answer. https://learn.microsoft.com/en-us/azure/architecture/solution-ideas/articles/iot-using-cosmos-db Azure Cosmos DB is ideal for IoT workloads because it's capable of: - Ingesting device telemetry data at high rates, and return indexed queries with low latency and high availability. - Storing JSON format from different device vendors, which provides flexibility in payload schema. - By using wire protocol–compatible API endpoints for Cassandra, MongoDB, SQL, Gremlin, etcd, and table databases, and built-in support for Jupyter Notebook files.

C. Azure Cosmos DB for NoSQL D. Azure Time Series Insights

MongoDB...

CD is correct.

Seems correct.

CD Real-time access with fast read and write latencies globally, and throughput and consistency all backed by SLAs https://learn.microsoft.com/en-us/azure/cosmos-db/introduction Azure Time Series Insights is a fully managed analytics, storage, and visualization service that makes it simple to explore and analyze billions of IoT events simultaneously. https://learn.microsoft.com/en-us/azure/time-series-insights/time-series-insights-explorer