5 min data storage approach in Azure decision tree
Case:
https://docs.microsoft.com/en-us/learn/modules/choose-storage-approach-in-azure/
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
