Azure Blobs
Large amounts of unstructured data, including log files, documents, photos, videos, and audio files, are kept in Azure Blobs, a data service. Blobs can be accessed via a URL or a REST API and are arranged into "containers," which are akin to folders. Versioning capability, which enables you to maintain several versions of a blob and access them as necessary, is one of Azure Blobs' core features. This can be helpful if you need to keep track of the changes made to your data or if you want to go back to a prior version in case something goes wrong. Integration with other Azure services, like Azure Functions, Stream Analytics, and Machine Learning, is another beneficial aspect of Azure Blobs. By doing this, you can use Azure Blobs as the data source for these services, giving you the ability to manipulate, analyse, and change the data. Azure Blobs can store and handle huge volumes of unstructured data, including multimedia files, documents, and log files, depending on the use case.
As it offers high scalability and dependability, it can be particularly helpful for businesses that need to store and manage massive volumes of data. Data that must be accessed often, such pictures and videos used on a website or application, can also be stored in Azure Blobs. In the same vein, providing and storing media material is another use case for Azure Blobs. A media corporation might, for instance, utilise Blobs to store big audio or video files and then use the Blob service to stream this content to viewers as needed. It is simple to combine the Blob service with other systems, such as a content delivery network (CDN), thanks to the ability to access blobs through HTTP or HTTPS.
This enables the media organisation to distribute material fast and reliably to users all over the world. Keeping vast amounts of data for analysis is one frequent use case for Azure Blobs. Blobs can be used by a business to store data that has to be processed and evaluated, such as log files, machine learning models, or other types of data. The organisation may then obtain insights and make data-driven choices by accessing and processing this data using Azure HDInsight, Azure Databricks, or other big data and analytics services.