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5 min data storage approach in Azure decision tree


Data classification:
The key factors to consider in deciding on the optimal storage solution are: how to classify your data, how your data will be used, and how you can get the best performance for your application.

  • Structured (SQL, RDBMS)
  • Semi-structured (key/value, NOSQL, serialization language, XML,JSON, YAML)
  • Unstructured (media, word, text, log)

What are the main operations on the data, ACID-compliant?
OLTP (Online Transaction Processing)
OLAP (Online Analytical Processing)

Correct storage solution can lead to better performance, cost savings, and improved manageability, after data classification.

Data classification: Semi-structured
Azure Cosmos DB
Azure SQL Database

Data classification: Unstructured
Azure Blob storage

Data classification: Structured
Azure SQL Database

Storage service

Storage service:

Storage account contains all Azure storage data objects: blobs, file shares, queues, tables, and disks.

  • Blob storage, object storage solution, storing massive amounts of unstructured data, text or binary data.
  • Data Lake Storage Gen2, big data analytics, Azure Blob Storage
  • Azure Files. file shares, SMB
  • Queue storage, storing large numbers of messages, commonly used to create a backlog of work to process asynchronously
  • Table storage, non-relational structured data, NoSQL, key/attribute store with a schemaless design.

Data store decision tree – Azure Application Architecture Guide | Microsoft Docs

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