Azure Table Storage Management

Azure Table Storage is a NoSQL key-attribute store that you can use to store large amounts of structured, non-relational data. It's a cost-effective solution for applications that need to store and query large datasets with a flexible schema.

Key Concepts

  • Tables: A collection of entities.
  • Entities: A set of properties, similar to a row in a database. An entity can have up to 100 properties.
  • Properties: A name-value pair. Property names are strings, and property values can be of various primitive data types.
  • Partition Key: A string that determines the table partition where an entity is stored. Entities with the same partition key are co-located.
  • Row Key: A string that uniquely identifies an entity within a partition.

When to Use Table Storage

  • Storing semi-structured data without a complex schema.
  • Handling large volumes of data for applications like IoT devices, user profiles, or product catalogs.
  • When fast query performance is needed for specific keys (Partition Key + Row Key).
  • When cost-effectiveness is a priority for data storage.

Operations and Management

Azure Table Storage supports standard CRUD (Create, Read, Update, Delete) operations. You can manage Table Storage using various tools and SDKs:

Azure Portal

The Azure Portal provides a visual interface for managing your storage accounts and tables. You can create tables, add/edit entities, and monitor usage.

Azure CLI & PowerShell

Automate your storage management tasks with powerful command-line tools.

Example: Creating a Table using Azure CLI

This command creates a new table named 'Products' in your storage account.


az storage table create --name Products --account-name mystorageaccount --account-key "YOUR_ACCOUNT_KEY"

Example: Inserting an Entity using Azure SDK (Python)

This Python code snippet demonstrates how to insert a new product entity into a table.


from azure.data.tables import TableClient

connection_string = "YOUR_CONNECTION_STRING"
table_name = "Products"

table_client = TableClient.from_connection_string(connection_string, table_name)

entity = {
    "PartitionKey": "Electronics",
    "RowKey": "SKU123",
    "Name": "Laptop",
    "Price": 1200.50,
    "InStock": True
}

created_entity = table_client.upsert_entity(entity)
print(f"Entity inserted: {created_entity}")

Performance Considerations

Optimize your queries by designing effective Partition Keys and Row Keys. Queries that filter on the Partition Key are highly efficient. Queries that span multiple partitions can be slower.

Pricing

Azure Table Storage is priced based on data storage and transaction costs, making it a very cost-effective solution for large datasets.

For detailed information on pricing, please refer to the Azure Storage Pricing page.