AWS storage types

Object storage

In object storage, data is stored in an unstructured manner. This means the data is not organized in a predefined format, such as a database table or a file system hierarchy. Instead, each object is stored as a self-contained unit with data, metadata, and a globally unique identifier (GUID).

The fact that the data is not divided is the key advantage of object storage. It allows for very efficient storage of large and complex datasets. For example, a single object can contain a video file along with its associated metadata, such as the title, duration, and resolution. This allows for the video file to be stored and retrieved efficiently without the need to break it down into smaller parts.

Example

Amazon S3 is an ideal example of object storage. It’s a highly scalable and durable storage service that can store data at any scale. Amazon S3 objects are stored in buckets, which are logical containers for objects. Each object has a unique GUID, which allows it to be accessed directly from anywhere in the world.

Here’s an example of how object storage might be used. Suppose a company has a website that hosts many images. The company uses Amazon S3 to store the images. Each image is stored as a single object with its data, metadata, and GUID. When a user visits the website, the images are retrieved from Amazon S3 and displayed on the page.

Use cases

Object storage is a very powerful and flexible storage solution. It’s well-suited for a wide range of applications, including website hosting, media file storage, data backup and recovery, disaster recovery, machine learning (ML), artificial intelligence (AI), and big data analytics.

Block storage

In block storage, data is stored in a structured manner. This means the data is organized in a predefined format, such as a database table or a file system hierarchy. Block storage is ideal for applications that require low latency and high performance, such as databases, virtual machines, and containerized applications.

The key advantage of block storage is that it allows for parallel processing. This means that multiple users can read and write to the same block of data simultaneously. This is important for applications that handle a high volume of concurrent requests.

Example

Elastic Block Store (EBS) is an ideal example of block storage. It is a highly scalable storage service that can store data for EC2 instances. EBS volumes can be attached to EC2 instances and used to store any type of data, including operating systems, databases, and application files.

Here’s an example of how block storage might be used: A company has a database that needs to be able to handle a high volume of concurrent requests. The company uses EBS to store the database. The database is installed on an EBS volume and attached to an EC2 instance. The EC2 instance is configured to use parallel processing so that multiple users can access the database simultaneously.

Use cases

Block storage is a very powerful and flexible storage solution. It’s well-suited for a wide range of applications, including databases, virtual machines, containerized applications, and high-performance computing.

File storage

Parallel processing is feasible in file storage but to a lesser extent than block storage. This is because file storage systems typically need to maintain a filesystem hierarchy, which can add some overhead to parallel operations.

But there are a number of techniques that can be used to improve the performance of parallel processing in file storage, such as using a distributed file system, caching, and parallel I/O, which can improve the performance of parallel operations by allowing multiple servers to process requests simultaneously and can reduce the latency of parallel operations.

Example

Here’s an example of how parallel processing might be used in file storage. Suppose a company has a file server that stores many video files. The company uses a distributed file system to store the videos across multiple servers. When a user requests a video file, the file server can distribute the request to multiple servers, which can then process the request simultaneously. This allows the file server to deliver the video file to the user quickly, even if the file is large and there are many other users requesting files at the same time.

Use case

Overall, parallel processing can be used to improve the performance of file storage systems, but it is important to choose a file storage system that is designed for high performance and supports parallel processing.

The difference between these storage types is given below:

Solve the following quiz to test your learning: