Which database type should be used to store data received from model-driven telemetry?
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A. B. C. D.B.
Model-driven telemetry is a technique for collecting and forwarding telemetry data from network devices to a central location for analysis and monitoring. It enables real-time analysis of network performance and provides insights for proactive network management.
To store the data received from model-driven telemetry, the database type should be selected based on the requirements of the application and the nature of the data.
The answer to the question depends on the specific use case, but here is a brief overview of the four options:
A. BigQuery database: BigQuery is a cloud-based data warehouse provided by Google. It is designed to handle large amounts of data and enable analysis of data in real-time. If the application requires real-time analysis of telemetry data, then BigQuery may be a good option. However, it may not be the best fit for all use cases, as it is a cloud-based service and may not be suitable for all types of data.
B. Time series database: Time series databases are optimized for handling data that is timestamped, such as telemetry data. They enable efficient storage and retrieval of time-based data and are designed to handle large amounts of data. If the application requires storage and retrieval of telemetry data based on time, then a time series database may be a good option.
C. NoSQL database: NoSQL databases are designed to handle unstructured data and are often used in applications where flexibility and scalability are important. If the telemetry data is unstructured or if the application requires a flexible schema for storing and querying telemetry data, then a NoSQL database may be a good option.
D. PostgreSQL database: PostgreSQL is a relational database management system that is widely used in enterprise applications. It supports a wide range of data types and enables efficient storage and retrieval of data. If the application requires a relational database for storing telemetry data, then PostgreSQL may be a good option.
In summary, the best database type to store data received from model-driven telemetry depends on the specific requirements of the application and the nature of the data. A time series database is a good option if the data is timestamped, a NoSQL database is a good option if the data is unstructured or requires a flexible schema, BigQuery may be a good option if real-time analysis is required, and PostgreSQL is a good option if a relational database is required.