Object storage vs. block storage

Object storage and block storage are two storage ar­chi­tec­tures that differ sig­ni­fic­antly in structure, access, and purpose. The key dif­fer­ence between object storage and block storage is that the former stores data as objects with metadata via an API, while the latter divides data into ad­dress­able blocks managed directly via the operating system.

What are object and block storage?

Object storage is a modern storage ar­chi­tec­ture where data is stored as objects. Each object consists of the actual data, metadata, and a unique iden­ti­fi­er. These objects are stored in a flat namespace. This means that all stored objects are organised at the same level. There is no hier­arch­ic­al structure like folders or dir­ect­or­ies, like in file systems. The data objects in object storage are typically ac­cess­ible via an HTTP-based API.

Block storage on the other hand divides data, as the name suggests, into equally sized, fixed blocks each with a unique address. Each block includes only the raw data, without ad­di­tion­al metadata or context in­form­a­tion. The system accessing this data – usually an operating system or a vir­tu­al­isa­tion platform – is re­spons­ible for in­ter­pret­ing the structure and meaning of the stored data. From the operating system’s per­spect­ive, block storage behaves like a physical hard drive or SSD: It can be par­ti­tioned, formatted, and used for various ap­plic­a­tions.

Object vs. block storage at a glance

In the following table, you’ll find an overview of the main dif­fer­ences of ‘Object storage vs. block storage’ in direct com­par­is­on:

How object and block storage work

Object storage saves data as three-part objects:

• actual user data (e.g., an image or a video)
• metadata (ad­di­tion­al in­form­a­tion like creation date, file type, or custom tags)
• unique key serving as an address

These objects are stored in a flat namespace. Tech­nic­ally, this is simpler and more scalable because there’s no need to manage a complex directory structure. Access is via the HTTP protocol, usually through REST. APIs. Ap­plic­a­tions interact with the storage like a web service. Many cloud services, such as Amazon S3 or Google Cloud Storage, are based on this tech­no­logy. Object storage can be dis­trib­uted worldwide, allowing data to reside at multiple locations sim­ul­tan­eously. This enhances both fault tolerance and global avail­ab­il­ity.

Block storage functions more like a tra­di­tion­al drive or hard drive. Here, data is divided into equally sized blocks, each assigned an address. These blocks contain no metadata. This means it’s the re­spons­ib­il­ity of the operating system or an ap­plic­a­tion on top (e.g., a file system or a database) to know which blocks belong together. Block storage is often provided via a Storage Area Network (SAN) or through the iSCSI network protocol. The storage then appears to the operating system like a local drive and can be par­ti­tioned, formatted, and written to normally.

Dif­fer­ences and sim­il­ar­it­ies between object storage vs. block storage

Although object storage and block storage both serve data storage purposes, they fun­da­ment­ally differ in structure, access, and usage. The biggest dif­fer­ence lies in how data is organised. In terms of latency and per­form­ance, block storage has a few ad­vant­ages because it allows for fast, block-level access. Object storage, on the other hand, excels in scalab­il­ity and long-term data retention.

Both storage types share the fact that they are often used in cloud en­vir­on­ments and, through their re­spect­ive spe­cial­iz­a­tions, can ef­fi­ciently support different workloads. Both can be part of a blended storage approach. Also, in terms of re­li­ab­il­ity and fault tolerance, modern im­ple­ment­a­tions of both tech­no­lo­gies offer important mech­an­isms like rep­lic­a­tion and re­dund­ancy. While block storage is more per­form­ance and direct-control oriented, object storage offers a flexible and cost-effective solution for large data volumes. In modern IT en­vir­on­ments, both types of storage are often combined to make the most of their re­spect­ive ad­vant­ages.

Typical use cases

Use cases for object storage

Object storage is fre­quently used for backing up and archiving solutions. Its high scalab­il­ity and cost-effective storage make this storage solution ideal for long-term data retention. It’s also popular in content delivery networks (CDNs), as large media files can be easily and ef­fi­ciently dis­trib­uted.

Another important use case is the storage of big data, such as log files, sensor data, or video re­cord­ings, since the objects can be stored and processed in­de­pend­ently. Modern web apps and mobile ap­plic­a­tions also use object storage to store user files, images, and documents.

Use cases for block storage

Block storage is the preferred solution for databases and trans­ac­tion­al systems. The ability to directly access blocks ensures high per­form­ance and low latency. These char­ac­ter­ist­ics are es­pe­cially important for ap­plic­a­tions that require frequent reading and writing of data at the same time.

Virtual machines and operating systems also benefit from using block storage, as they rely on fast and reliable storage. Even in tra­di­tion­al data centres, where de­term­in­ist­ic per­form­ance is crucial, block storage is still widely used.

Ad­vant­ages and dis­ad­vant­ages

In a direct com­par­is­on of object storage vs. block storage, the ad­vant­ages and dis­ad­vant­ages play an important role.

Object storage offers high scalab­il­ity, easy in­teg­ra­tion through web APIs, and the ability to store extensive metadata for each object. This makes it par­tic­u­larly well-suited for un­struc­tured data and cloud-native ap­plic­a­tions. However, access is com­par­at­ively slow, so object storage is not as suitable for ap­plic­a­tions where low latency is important.

Block storage, on the other hand, offers sig­ni­fic­antly lower latency and par­tic­u­larly im­press­ive per­form­ance. The direct in­teg­ra­tion with virtual machines or con­tain­ers also makes block storage the first choice for tra­di­tion­al IT in­fra­struc­tures. However, this comes with higher costs and less flex­ib­il­ity in handling large, dis­trib­uted data sets.