Table storage

Overview

Scalable NoSQL storage for flexible, structured data

Use Azure Table storage to store petabytes of semi-structured data and keep costs down. Unlike many data stores—on-premises or cloud-based—Table storage lets you scale up without having to manually shard your dataset. Availability also isn’t a concern: using geo-redundant storage, stored data is replicated three times within a region—and an additional three times in another region, hundreds of miles away.
Table storage is excellent for flexible datasets—web app user data, address books, device information, and other metadata—and lets you build cloud applications without locking down the data model to particular schemas. Because different rows in the same table can have a different structure—for example, order information in one row, and customer information in another—you can evolve your application and table schema without taking it offline.
Table storage embraces a strong consistency model. When data is inserted or updated in Table storage, all further accesses to that data will see the latest update. This is critical for systems with multiple users who are simultaneously updating data stores.
Azure Storage provides rich client libraries for building apps with .NET, Java, Android, C++, Node.js, PHP, Ruby, and Python. The client libraries offer advanced capabilities for Table storage, including OData support for querying and optimistic locking capabilities. Data in Azure Storage is also accessible via the REST API, which can be called by any language that makes HTTP/HTTPS requests.