Choosing the right storage solution is important for setting up your business on the right track. This decision should be primarily based on the workload you expect to deal with. Object storage and block storage are popular solutions with certain benefits and limitations.
Read on to learn more about how they differ and when to use one over the other.
Object Storage vs. Block Storage: Overview of the Difference
Before examining each storage option individually, let’s take a look at some of the main differences between object storage and block storage.
|Point of Comparison
|Unique, identifiable, and distinct units called objects store data in a flat-file system.
|Fixed-sized blocks store portions of the data in a hierarchical system and reassemble when needed.
|Unlimited, customizable contextual information.
|Limited, basic information.
|Suitable for high volumes of unstructured data. Performs best with large files.
|Best for transactional data and database storage. Performs best with files small in size.
|A centralized or geographically dispersed system that stores data on-premise, private, hybrid, or public cloud.
|A centralized system that stores data on-premise or in private cloud. Latency may become an issue if the application and the storage are geographically far apart.
The biggest change from traditional block storage to object storage was modifying the way data is stored. Block storage includes splitting a file into data blocks that contain portions of the information. The data blocks are stored in a hierarchical system on one or multiple drives and accessed via performance protocols.
In opposition, object storage stores files as modular units in a single repository (bucket) using a flat-file system. Each object represents a self-contained, identifiable, distinct unit that can be located at several (changeable) locations.
The crucial difference between object storage and block storage is the amount of metadata the data units hold. Apart from basic information such as owner, size, and date of creation, object storage includes additional contextual information. As metadata is customizable and unlimited, the data is easily organized and managed to contribute to effective data analytics.
When it comes to cost, block storage is the more expensive storage solution. As blocks are fixed in size, purchasing additional storage to scale out includes additional expenses. For this reason, many organizations with high volumes of data opt for object storage.
As the number of files and users grows, block storage gains complexity and it takes more effort to find a particular file. At some point, this hinders performance as the system reaches its file-limit. Planning long-term capacities is more difficult with block storage. An organization might end up overpaying for idle resources or need further capacities sooner than anticipated.
On the other hand, thanks to its flat structure, object storage allows scaling out simply by adding new nodes to the structure.
Block storage provides better storage performance than its counterpart. This is mainly due to the way it stores units of data. Since data is split into subsequent data blocks, block storage allows modifying (or retrieving) only part of a file instead of the entire unit.
On the other hand, object storage requires rewriting the whole file as data is not partitioned. Hence, block storage is mainly used for transactional data and databases, while object storage performs best when dealing with high volumes of unstructured data.
Note: Object storage is unsuitable for data sets where files are modified frequently. In such cases, there is no guarantee that a retrieve request returns the most recent version of the data.
Object storage is a single system that spreads across several locations. Every object has its own unique identifier and there is no need to know the location of the data to access it. Administration of data is conducted over an HTTP/S interface.
Block storage has a centralized system in which it stores data on-premises or in a private cloud. Knowing where a file is located is necessary to access it.
What is Object Storage?
Object storage is a storage method in which data is organized, managed, and manipulated as unique, identifiable, and distinct units called objects. It is quite different than the traditional approach and emerged due to the growing demand for a practical way to store large amounts of unstructured data.
Instead of a hierarchical file system, object storage has a flat-file system for storing data. All objects are kept as self-contained units in a single-level repository called a bucket.
Each object consists of the data it stores, comprehensible metadata, and a unique identifier. The metadata provides contextual information about each object, while the identifier helps locate the object within a distributed system.
The main advantages of object storage are its scalability and the ability to store large collections of unstructured data. Thanks to its flat structure, this storage method provides unlimited scalability by adding new nodes to the cluster. Additionally, it can handle storing and retrieving high volumes of data in record times.
Note: To learn more about this data storage solution, check out What is Object Storage.
Object Storage Use Cases
Object storage is mainly used for:
- Storing big data. Object storage, due to its metadata capabilities, scalability, and robust API works excellent for machine learning. Storing and accessing unstructured data is where object storage excels at.
- Creating backup copies and archives. Object storage is a reliable option for data sets that aren’t updated often. Users who are not leveraging a supported backup utility (Veeam, R1Soft) can leverage the S3 interface for their backups.
- Media and entertainment data storage. This storage solution excels at storing high volumes of images, graphics, video, or audio files. Most importantly, it makes them accessible to users anywhere in the world at lightning speed.
- Data storage with ransomware protection. Object storage creates a new version of the same file after each modification allowing you to restore data in case of a ransomware attack.
- Storing personal medical files. Thanks to its built-in security and resilient replication, object storage is used for protecting personal medical data. Additionally, some object storage solutions are HIPAA-compliant by default, a critical factor when storing personal medical files.
- Hosting a Static Website. Object storage is a suitable environment for hosting a static website that scales automatically to meet traffic demands. Using object storage
Note: A static website presents the same content to all visitors. There is no content-personalization based on cookies. A static website does not use server-side scripting.
What is Block Storage?
Block storage is a form of data storage that splits data into fixed-sized units called blocks. Each block stores a portion of the data and has a unique identifier used to reassemble it when needed. These unique addresses can also store blocks separately across multiple machines.
Data blocks are allocated and managed using software, separated from the storage device. When retrieving a file, you send a block request through a performance protocol, such as iSCSI or FCoE. Once the required addresses are found, the blocks are organized to form a complete file.
Unlike objects, data blocks have limited metadata. While including basic specifications (the size, owner, and creation date), traditional storage doesn’t store additional information about the data. Therefore, block storage needs more time to locate the required data in metadata-critical operations, which inevitably affects the overall performance.
Still, block storage generally has low latency and is great for apps that require a high number of input/output operations. It has great performance scores and speed compared to other solutions. A factor that can influence performance is where the data is being stored. The system retrieves files faster or slower depending on whether the application and data are stored locally or farther apart. Traditional block storage, however, is slow in retreating unstructured data.
Block Storage Use Cases
Block storage is primarily used for:
- Database storage. Object storage provides consistent I/O performance, low latency, redundancy, and fault tolerance, making them ideal for resource intensive database applications.
- Storing data for applications that require service-side processing. Applications that require server-side processing (such as Java, PHP, and .Net) require using block storage.
- RAID volumes. RAID arrays are a common use case for block storage as this storage solution stores data on multiple disks organized by stripping or mirroring. Therefore, you can employ block storage as RAID volumes.
- Container storage. Block storage help with managing data stored in Docker or Kubernetes container by separating the data from the lifecycle of the container or pod and providing fixed-sized persistent storage.
- Storing mission-critical applications. Block storage is a common choice for applications that deal with mission-critical data. Its excellent performance and low latency ensure the app functions continuously as required.
Deciding Between Object Storage and Block Storage
Both storage solutions offer great features which are more or less beneficial depending on the use case.
Object storage is best used for large amounts of unstructured data, especially when durability, unlimited storage, scalability, and complex metadata management are relevant factors for overall performance.
Block storage provides low latency and high-performance values in various use cases. Its features are primarily useful for structured database storage, VM file system volumes, and high volumes of read and write loads.
phoenixNAP object storage enables you to store and process exabytes of data. With built-in native S3 support, easily manage and access your data through simple S3 API calls. Check out how to leverage phoenixNAP's cloud object storage to store and scale all types of data across multiple geographic locations.