Comparison of Object and File storage with AccuWeb.Cloud
Your organization’s data is one of its most valuable assets, so selecting the right storage solution is crucial. But with so many options, how do you decide which type of storage to use?
Typically, you can choose from three main types of storage: object storage, backup storage, and file storage. Each type has its way of storing, organizing, and presenting data, making them suitable for different needs and business scenarios.
Understanding these primary storage types is essential, as the choice you make will affect how easily you can access and manage your data.
In this guide, we’ll explore the basic comparison between object storage and file storage, including what kinds of data they handle and their storage methods.
What is Object Storage?
Object storage is a method of storing data where each piece of data is kept in separate units known as objects. These objects include a unique identifier and metadata that describes the data, making it easier to access and retrieve compared to other storage types.
Unlike file storage, object storage doesn’t use a hierarchy of folders or directories. Instead, objects are kept in a flat storage environment, often called a storage pool.
While objects can be stored locally, they are typically stored in the cloud, allowing organizations and teams to access data from anywhere. To retrieve an object, the system utilizes its unique identifier and metadata.
This flat storage model is particularly effective for managing large volumes of unstructured data, like social media content, videos, or sensor data, which don’t fit well into a hierarchical structure.
Additionally, object storage is highly scalable. Data is organized within a single global storage pool, making it easy to access and manage even if it spans multiple hardware devices and locations.
Common uses for object storage include cloud-native applications, Internet of Things (IoT) data, big data, rich media storage and delivery, as well as backups and archives.
Pros of object storage
- Massive scalability: Object storage offers near-limitless scalability, allowing you to add more devices and expand storage capacity as needed.
- Ideal for big data: Object storage simplifies the management of large volumes of unstructured data, making it perfect for big data applications such as AI, machine learning, and predictive analytics.
- Simplified data retrieval: Object storage eliminates the need for traditional folders and directories, making it easier to access data without knowing its exact location.
- Cost-effective on-demand storage: With a consumption-based pricing model, you only pay for the storage you use. This scalability helps manage costs efficiently while storing all your data.
- Enhanced searchability: Object storage provides advanced search capabilities, enabling you to find objects based on metadata, content, and other attributes.
Cons of object storage
Despite the growing popularity of object storage, particularly in cloud environments, it does have some limitations. For instance, it’s not the best choice for transactional data since writing data takes a bit longer compared to file or block storage.
Another drawback is that once an object is created, it can’t be modified. Any changes require you to recreate and upload the entire object.
What is File Storage?
File storage organizes data using a system of files and folders, much like a physical filing system. Data is stored in individual files, which are then placed in folders. These folders are further organized into subdirectories and directories. Each file is identified by its name, type (file extension), and the path to its location.
This method mirrors how documents are organized in a physical office, with a clear hierarchy. It’s the most established and widely used storage system, likely familiar to you from your personal computer.
File storage simplifies finding and retrieving specific data items and can accommodate almost any type of data. However, to locate a file, the system needs the exact path, including the sub-directory and file name. As the volume of data grows, managing and efficiently using file storage can become challenging and time-consuming.
Despite these challenges, file storage remains popular due to its familiarity. It’s commonly used for web content management, collaborative file and document storage, and small-scale local file storage.
Pros of file storage
- Straightforward and convenient storage: Even those with basic computer skills can effortlessly navigate file storage systems to locate information without requiring extra training.
- Intuitive management: Users can create, manage, and delete their own files independently with file storage. Additionally, it offers simple access management, allowing users to control who can access, view, and modify files.
- Established protocols: File storage systems utilize standard computing protocols like Network File System (NFS), Common Internet File System (CIFS), or Server Message Block (SMB).
Cons of File Storage
As noted earlier, file storage systems are efficient up to a certain limit. However, as the volume of files, folders, and directories increases, accessing and managing data becomes increasingly challenging. With a growing amount of data, the search functionalities can become inefficient, causing delays that may hinder employee productivity.
Although file storage can technically accommodate unstructured data, it is generally not designed for managing extensive quantities of such data. Additionally, scaling up to meet storage demands can be costly, as it typically requires the purchase of new storage hardware.
Key Differences Between Object Storage and File Storage
When deciding between object storage and file storage for your data, you can consider the following:
| Object storage | File storage | |
| Type of storage | Objects stored in scalable buckets | Files are organized hierarchically in folders and directories |
| Volume of data | Supports high data volumes | Better for lower volumes of data |
| Data management | Custom metadata provides easy searchability | Hierarchical structure works well for simpler, smaller datasets |
| Cost | Pay-as-you-go pricing, more cost-effective | More costly, requires purchasing new storage devices to scale out |
| Performance | Slower performance, longer processing times | Performance impacted by higher data volume |
| Scalability | Highly scalable | Limited scalability |
| Ideal for | Big data storage, static unstructured data, analytics, rich media files, and backups | Shared file storage, unstructured data |