With object storage, the data blocks of a file are kept together as an object, together with its relevant metadata and a custom identifier, and placed in a flat data environment known as a storage pool. 

When you want to access data, object storage systems will use the unique identifier and the metadata to find the object you need, such as an image or audio file. You can also customize metadata, allowing you to add more context that is useful for other purposes, such as retrieval for data analytics.  

You can locate and access objects using RESTful APIs, HTTP, and HTTPS to query object metadata. Since objects are stored in a global storage pool, it’s fast and easy to locate the exact data you need. Plus, the flat environment enables you to scale quickly, even for petabyte or exabyte loads. Storage pools can be spread across multiple object storage devices and geographical locations, allowing for unlimited scale. You simply add more storage devices to the pool as your data grows. 

The benefits of object storage, like its elasticity and scalability, have made it an ideal fit for managing unstructured data in cloud infrastructure. So, what is object storage in the cloud? It’s exactly what it sounds like—object-based storage as an on-demand cloud service. In fact, cloud object storage is the primary storage format for most major cloud service providers.

Over time, the world’s data storage needs have evolved with the introduction of the internet and an expanding list of data sources and types. Traditional file storage and block storage aren’t well-suited to handle the enormous amount of data being generated, especially unstructured data that is not made to fit into structured data storage methods. 

So, how does object storage compare to file storage and block storage?

File storage stores and organizes data into folders, similar to the physical files you might store in a paper filing system in an office. If you need information from a file, you’ll need to know what room, cabinet, drawer, and folder contains that specific document. This same hierarchical storage structure is used for file storage, where files are named, tagged with metadata, and then placed in folders. 

To locate a piece of data, you’ll need to know the correct path to find it. Over time, searching and retrieving data files can become time-consuming as the number of files grows. While scalability is more limited, it is a simple way to store small amounts of just about any type of data and make it accessible to multiple users at once. 

Block storage improves on the performance of file storage, breaking files into separate blocks and storing them separately. A block-storage system will assign a unique identifier to each chunk of raw data, which can then be used to reassemble them into the complete file when you need to access it. Block storage doesn’t require a single path to data, so you can store it wherever is most convenient and still retrieve it quickly when needed. 

Block storage works well for organizations that work with large amounts of transactional data or mission-critical applications that need minimal delay and consistent performance. However, it can be expensive, offers no metadata capabilities, and requires an operating system to access blocks. 

Object storage, as discussed earlier, saves files in a flat data environment, or storage pool, as a self-contained object that contains all the data, a unique identifier, and detailed metadata that contains information about the data, permissions, policies, and other contingencies. Object storage works best for static storage, especially for unstructured data, where you write data once but may need to read it many times. 

While object storage eliminates the need for directories, folders, and other complex hierarchical organization, it’s not a good solution for dynamic data that is changing constantly as you’ll need to rewrite the entire object to modify it. In some cases, file storage and block storage may still suit your needs depending on your speed and performance requirements.