Cloud Storage Three Ways: File vs. Block vs. Object
Let’s compare the three main types of storage available in cloud computing: block storage, file storage, and object storage. Along with exploring their key concepts, we'll cover how to choose the right storage option for your requirements.
Michael Nicholson
Cloud Solution Engineer
In this article, I'll compare the three main types of storage available in cloud computing: block storage, file storage, and object storage. By the end of the post you'll understand the concepts involved with each type of storage, and when it is appropriate to choose one type over another.
File Storage
File storage is a method of organizing data in a hierarchical file system. Files of any type are stored within directories/folders, which can be nested within other directories to create a structured data organization. This will likely be the most familiar storage method, simply because it is the method everybody is used to on their local computers, whatever brand they may be or whatever flavor operating system they may be running.
File Storage Options From The Big Three
Key Characteristics
Simple to use and understand.
Supports standard file operations, like read, write, and modify.
Suitable for any application that requires file sharing and collaboration.
Pros:
Easy to implement and manage.
Supports file sharing across multiple instances.
Familiar file system structure.
Cons:
Slower performance compared to block storage.
Limited scalability and flexibility.
Why Is The Scalability And Flexibility Limited When Using File Storage?
This limitation is largely due to the inherent hierarchical structure, which organizes data in nested directories or folders, and creates a few limitations:
Performance: As the amount of data and the number of nested folders increase, accessing and managing files can become slower, which in turn leads to performance bottlenecks.
Capacity Constraints: File storage systems may have predefined limits on the number of files, folders, or the overall storage capacity. This may not be immediately obvious for new applications, but it can be difficult to scale up as storage requirements increase.
Distribution Limitations: File storage systems are typically less efficient at distributing data across multiple geographic locations compared to object storage, which uses a flat address space.
These limitations can mean file storage is less suitable for applications requiring high levels of scalability, flexibility, or data distribution.
Block Storage
Block storage is a method of storing data in fixed-sized blocks, or chunks, that are individually addressable. Each block has a unique identifier, which allows for fast and efficient read and write operations.
Block Storage Options From The Big Three
Key Characteristics:
High performance and low latency.
Suitable for databases, virtual machines, and other applications that require fast read/write access.
Pros:
Fast and efficient data access.
Scalable storage capacity.
Can be used with multiple operating systems.
Cons:
Generally more expensive than other storage options.
Not optimised for unstructured or distributed data.
Why is Block Storage Not Optimised For Unstructured Or Distributed Data?
The design of block storage focuses on fixed-sized blocks and low-latency access. This design creates a few limitations for handling unstructured or distributed data:
Fixed Block Sizes: Fixed-sized blocks may not be suitable for storing varying sizes of unstructured data, like images, videos, or text documents. Unstructured data can lead to inefficient use of storage, as blocks may not be fully used, wasting storage capacity.
Inefficient Data Access: Block storage is designed for fast, low-latency read and write operations, making it ideal for applications like databases and virtual machines. However, unstructured data often involves infrequent or large-scale access patterns that don't benefit from the low-latency characteristics of block storage, resulting in less-than-optimal performance and potentially increasing costs.
Limited Distribution Capabilities: Block storage systems are typically less adept at distributing data across multiple geographic locations compared to object storage, which uses a flat address space and is specifically designed for high scalability and distribution.
Due to these limitations, block storage is less suitable for handling unstructured or distributed data, or for applications that require global data distribution or high levels of redundancy. If these are your requirements, then object storage is a better solution.
Object Storage
Object storage is a method of storing unstructured data as individual objects within a flat address space. Each object contains its data, metadata, and a unique identifier.
What Is Unstructured Data?
Unstructured data refers to information that does not have a predefined data model or organised format. This includes text, images, videos, audio files, and documents. Because there is no clear schema or structure, it is more complex to analyze and process than structured data.
What Is Meant By A Flat Address Space?
A flat address space refers to a storage system where all objects or data elements are stored in a single, non-hierarchical level. In this type of system, each object has a unique identifier, which is used to locate and access the data directly. Contrast this with hierarchical structures, like file systems, where data is organized using nested directories. Flat address spaces provide simplified access and improved scalability, making them well-suited for managing large amounts of unstructured data.
Object Storage Options From The Big Three
Key characteristics:
Highly scalable and cost-effective.
Ideal for large amounts of unstructured data, like images, videos, and documents.
Supports data distribution across multiple geographic locations.
Pros:
Easily scalable to accommodate growing data needs.
Efficient storage for unstructured data.
Accessible via API or web interface.
Cons:
Not suitable for applications requiring low-latency or high-performance data access.
More complex to manage compared to file storage.
Object Storage And Low-Latency Or High-Performance Data Access
The design of object storage focuses on scalability, cost-effectiveness, and handling unstructured data. This leads to a few limitations:
Higher Latency: Object storage systems typically have higher latency compared to block storage because they need to process additional metadata and unique identifiers associated with each object. This makes object storage less efficient for applications that require rapid data access, like databases or virtual machines.
Slower Data Access: In object storage, each object is stored independently with its metadata, requiring additional processing for read and write operations. This can result in slower data access compared to block or file storage, which have more optimised access patterns for specific use cases.
API-Based Access: Object storage usually relies on APIs or web interfaces for data access, which can introduce additional overhead and latency compared to direct access methods used in block and file storage.
These limitations mean object storage is less suitable for applications that demand low-latency or high-performance data access. Instead, use block storage for these scenarios, as this provides faster and more efficient read and write operations.
Object Storage Complexity Compared to File Storage
Object storage is more complex to manage compared to file storage for a few reasons:
Flat Address Space: Unlike file storage's familiar hierarchical structure with nested directories, object storage uses a flat address space where objects are stored independently. This can make it more challenging to organise and manage data compared to the directory-based organisation of file storage.
API-Based Access: In contrast to Object storage’s APIs or web interfaces for data access, file storage typically uses standard file operations like read, write, and modify. Users already familiar with file systems may find it more challenging to manage data using APIs compared to traditional file operations.
Metadata Management: Object storage stores customisable, extendable metadata with each object. This adds complexity to data management. File storage, on the other hand, uses a predefined set of metadata attributes, making it much easier to manage.
These factors make object storage more complex to manage compared to file storage, which offers a simpler, more familiar data organisation and access model.
Conclusion
When choosing the right storage solution for your cloud computing needs, it's important to consider the specific requirements of your application. Here's what each storage type can offer and what they're appropriate for:
Block storage offers high performance and low latency, making it suitable for databases and virtual machines.
File storage provides a familiar hierarchical structure, ideal for file sharing and collaboration.
Object storage is best for large amounts of unstructured data, offering scalability and cost-effectiveness.
Finally, here's a flowchart to help you making your choice between block storage, object storage and file storage.
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