Azure Data Fundamentals: Choosing the Right Data Store for High-Volume JSON Data with Application-Defined Schema

High-Volume JSON Data and Application-Defined Schema

Question

Your company is designing an application that will write a high volume of JSON data and will have an application-defined schema.

Which type of data store should you use?

Answers

Explanations

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A. B. C. D.

B

A key/value store associates each data value with a unique key.

An application can store arbitrary data as a set of values. Any schema information must be provided by the application. The key/value store simply retrieves or stores the value by key.

https://docs.microsoft.com/en-us/azure/architecture/guide/technology-choices/data-store-overview

Based on the requirement of writing high volume of JSON data with an application-defined schema, the best option is to use a document data store, which can efficiently handle semi-structured data like JSON.

Document databases like Azure Cosmos DB's Document API, MongoDB, or Amazon DocumentDB are designed to store and retrieve JSON documents, and are ideal for handling dynamic or evolving schema.

Here are some benefits of using a document data store:

  1. Flexible schema: Document data stores can handle data with dynamic and evolving schemas. This means that you can store data with different structures, fields, and attributes in the same database.

  2. Native support for JSON: Document data stores natively store and query JSON data, which makes it easy to write and retrieve JSON documents.

  3. High scalability: Document data stores are designed to handle large volumes of data, and can scale horizontally by adding more nodes to the database cluster.

  4. Rich querying capabilities: Document data stores offer powerful querying capabilities that can filter, sort, and aggregate data based on specific criteria.

Columnar data stores (A) are optimized for handling large datasets with many columns. Key/value stores (B) are simple databases that store data as key/value pairs and are not suitable for storing complex data like JSON documents. Graph databases (D) are ideal for handling data with complex relationships, such as social networks or recommendation systems. However, they are not suitable for storing large volumes of JSON data.