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Understanding Block Storage vs Object Storage

Block storage vs Object storage, which is the right fit for today’s data storage environments?

This question has probably left even the most experienced IT storage admins to scratch their heads. The reason? With enterprise data storage choices being Block, File storage, and Object, it’s often the Block Storage vs Object storage debate that collides. Blame it on the data at scale making future data storage a massive challenge. Processing the data, storing it, and accessing it based on the use cases — imagine the complexity it drives for the deployment of each type of architecture!

In this article, we shall discuss block storage vs object storage, the access methods, & their use cases. Again, each has its own capabilities and limitations. In this article, let’s delve deeper to understand how do they best fit into businesses why they might not be the best choice always.

Ready to dive in? Let’s explore.

Object Storage

To put it simply, object storage is a data storage architecture that lets you store distinct data units or objects as isolated containers. Since object storage has a flat address structure, you can store each object with equal access across multiple networked systems. The biggest perk of using such storage is that you can locate the object even without knowing the physical location of the data. Thanks to the set of attributes that object storage brings to the table. These are:

  1. The data. It can be anything you want to store ranging from a family photo, music, videos, 5,00000-page manual document file, to any unstructured data.
  2. Relevant metadata that describes the data (includes details like age, privacy, access contingencies); and
  3. A custom identifier that contains a unique ID address to let the OS locate it over a distributed system.

Access Methods

It’s important to realize that object storage uses APIs to access objects that rely on Representational State Transfer (RESTful) APIs. As a result, if you want to retrieve an archived file faster, you can easily send an API request to the cloud block storage to locate the desired object. This makes object-based storage a great choice for public cloud workloads. Furthermore, you can distribute objects across multiple geographic locations, by moving the objects across the different tiers.

Interestingly, Object storage lets you classify/organize the files with the file information and index it to retrieve the data whenever you want. However, you can access this data by mounting the drive volume through an OS server compatible with the object device. For example, AWS, the market leader of the cloud provides Amazon S3 is an object storage offering.

Use cases

Storing unstructured data

Since object storage follows no hierarchy, it’s ideal for storing data such as multimedia content, files, folders, archives, and static web content distributed across geographical locations.

Cloud application development

Object storage facilitates application availability by distributing networks. As a result, you can easily build & develop native system applications easily. Besides, you can easily store, tag, & analyze the data for big data analytics.

Archival storage

With object storage, you can add storage nodes for scaling unstructured data updated frequently. This allows you to archive files while still retaining instant access.

Backup of files

You can use object storage to backup files, log files, and database dumps.

Data can be read/write multiple times

In Object storage, data written once can be read by multiple devices. This works very well for globally distributed rich media storage as multiple clients can access and read/write data across all locations.

Optimized for static data

Once the data is written, it can be read many times. Henceforth, you can manage high volumes of static and unstructured data with object storage. For example, you can store images, video files, music, or transactional records as objects.

Why Object Storage for Businesses?

When it comes to the difference between Block storage vs Object storage, the former wins as a preferable option for unstructured data storage. Truly, unstructured data is complex to organize, manage, and search. This is where Object storage makes sense in extracting data insights from high-volume storage using metadata.

Below are the reasons for choosing object storage technology for your storage needs:

Searchability:

Metadata residing in the Objects themselves power extensive search results. For example, you can search for a certain type of file that meets specific criteria. Also, you can easily create custom metadata and add attributes over time without having to build databases to associate metadata with the objects.

Unlimited scalability:

Object storage lets you store a massive amount of data by adding multiple nodes to leverage storage space. Therefore, you can cater to on-demand scalability by mixing and matching high-density servers. This ensures the high availability of data as multiple copies of the same objects get dispersed across multiple nodes.

Big data analytics:

To take advantage of big data analytics, rely on object storage. That’s because each individual object is tagged with metadata that provides relevance by adding more context to the underlying data. Hence, you can extract actionable insights from the big data which you cannot expect from traditional blocks.

Distributed storage across geographies:

You can take advantage of distributed access feature of the multi-petabyte scale data storage bigtime! Thanks to extensible metadata and the geographic flexibility of object storage. With the keyword-searchable global namespace, you can easily locate, migrate, and protect the data. Another key point is that because of the workload distribution, you can deploy powerful functions across servers. This not only optimizes the capacity, cost, availability but also meets compliance requirements, thereby helping you meet your business goals.

Meets heavy data storage needs:

You can store large files, customer data, and unstructured enterprise data in a storage pool. It can scale hundreds of petabytes of data. This eliminates the scaling limitations because of flat namespaces – a very attractive option for enterprises.

Application development using HTTP(s) protocol:

Since Object storage supports access via HTTP(s) protocol, you can easily integrate it into your applications as all requests are made over HTTP(s) API. So, now you can build, develop, deploy cloud-native applications for mobile, responsive, and even traditional app development.

Why Object Storage Is Not the Best Choice Always?

To understand block storage vs object storage, you should assess the instances in which Object storage is not well suited. Here you go.

  • With Object storage, you cannot modify files as objects are designed to read/write or overwrite entire files, and not part of it. If you are uploading a new revision of the entire file, it affects the IO performance. Henceforth, it’s a bad choice for database operations.
  • Object storage doesn’t guarantee that you will receive the latest version of the file upon the read request. This is because updates distributed across all locations are not latest or (eventual consistent) always as data is not constantly altered.
  • For organizations that prioritize storage performance, object storage delivers slow I/O activity performance for workloads across the storage. Blame it on the object-based architecture that requires metadata analysis. Since data is bundled together with customized metatags, this slows down the performance of applications and workflows.

Block Storage

Block storage (also known as block-level storage) is the simplest form of data storage technology used for storing structured data such as databases, applications, etc. Since the storage is deployed in Storage Area Networks (SANs) systems, you can store complex files and applications with faster performance. Thanks to the structured workloads that let you access data faster. However, it supports the storage and applications that are locally accessed.

In block storage technology, you can split each block into equal-sized blocks that function like individual hard disk drives in a PC. Here, the blocks are controlled by an external server OS that lets you access these storage drives. This provides you more flexibility to store any kind of application including file, database, VM volumes, and more. What more, you can share the storage files or backup your data placed in the block storage using supported third-party tools. For example, AWS is Amazon Elastic Block Store (EBS) is a persistent block storage service designed for Amazon Elastic Cloud Compute (EC2).

Access Methods

If you are worried about restoring high-performing workloads, block storage has an answer to this. Access block-level data is simplified using high-performing protocols such as Fibre Channel and Internet Small Computer Systems Interface (SCSI) which makes data access faster.

Interestingly, each block has its unique ID address that lets you access, search specific data, or retrieve the block data quickly. Since the OS can directly read/write/re-write the blocks as needed, you can easily configure, manage and organize the data as a (structure) file system or an application-specific structure.

So now, you can easily restore data-intensive applications while reducing the software overhead. Also, you can easily modify the blocks to access specifically required blocks while keeping the older version intact.

Use Cases

Create raw storage volume for any application

With block storage, you can create individual hard drives for any application such as database, files, VM filesystem, and more.

RAID arrays

You can employ block storage systems as RAID volumes (*RAID is a data virtualization storage technology) that bolster data protection. This is done by configuring individual disks into RAID arrays.

Consistent I/O operations

You can use block storage for database-oriented applications that require a very low-latency and consistent storage operations I/O (Input/Output or Read/Write).

Email servers

Since block storage allows adding more capacity, you can use block storage for handling email servers such as Microsoft Exchange.

VMware servers

Using block-level storage, you can deploy VMware servers for storing VM filesystems (VMFS) volumes.

Booting

You can use a block storage architecture to boot up an operating system or external server directly from the block storage.

Why Block Storage for Businesses?

Why block-level storage makes sense for the IT environment?

Below are the reasons that makes block a popular choice for storage medium:

Versatility

You can format block-level storage to accept any usable filesystem. E.g, VMware servers will use VMFS; for running Windows, NTFS is the primary format.

Flexibility

Block storage allows quick configuration to update storage capacity. You can add storage volumes or move storage between servers without sacrificing performance.

Fast I/O data performance

Block storage mechanisms support underlying file protocols (NFS, CIFS, ext3/ext4, and others) for rapid I/O data access and low latency for high-performance applications. So, you can perform high-activity IO operations such as caching, database operations, log files, etc.

Add storage capacity

You can easily upgrade to standard speed storage by adding high-performance storage for customers.

Pay as you use

You just need to pay for the block storage space that you have allotted. This means you can easily attach/detach or reattach block storage volume that keeps your cost down.

Scale-out performance

Since block storage volume works independently with separate blocks of data, you can create additional block volumes to scale out. The performance scales with the disk size or the limit of the VM instances. The good news is that you don’t have to pay for more compute capability.

Easy management

You can easily manage access and control privileges as the host in the Operating system or block storage volumes directly control the data permissions.

Why Block-Based Storage, Not the Best Choice Always?

Block storage might not be the best alternative for some instances. Here’s why.

  • Since block storage architecture has no metadata, it has limited capability for data analytics. So, if you want to store metadata separately, you need an additional database. This retricts the client to access specific files from other servers at the same time.
  • Unlike tiered-based pricing, the entire block storage volume pricing is pre-defined. That is to say, to access one piece of data, you need to pay for the entire block storage space which includes the volume of data stored, types of operations performed, and data transfer cost. Indeed, this makes optimizing storage capacity for higher performance quite expensive.
  • In block storage, file distribution is complex as each unit of data is split and stored separately. As a result, you might end up with considerable wastage of compute instances of infrastructure costs. Besides, it might also lead to inefficient utilization of resources.
  • The SAN environment of block storage need expensive hardware to store data, thereby, making it more expensive to meet storage needs.

Take a quick look at the comparison chart that summarizes the difference between block storage vs object storage.

Object Storage
Block Storage
Data is stored as objects in scalable buckets. Data is stored as fixed-sized blocks.
Can scale infinitely to Petabytes and beyond. Limited scalability with fixed-sized blocks as per requirements.
With more context to data (metadata), you can easily organize, locate, or retrieve data. No metadata.
Unstructured data can be stored efficiently across multiple geographical locations. The greater the distance between storage, the higher the latency.
Best performance for unstructured content and high stream throughput. Best performance for relational database and transactional data.
HTTP(S) based API connectivity. Accessible via Fibre Channel and Internet Small Computer Systems Interface (iSCSI).
Unlimited file storage capacity. Can add nodes to increase capacity.
Best suited for static files and applications such as data backups, static content, archival images, rich multimedia content (videos, pictures, or music). Ideal for applications such as enterprise databases, and transactional data that require high IOPS and low latency.

Now that you know how one storage is overtaking the other, it’s safe to say that object-based storage is more suited for the IT storage environment. But, whichever storage option you are comfortable with, you are likely to store your data for long-term archival. This holds for data used less frequently, or not accessed at all but consumes a valuable storage place.

Whatever the storage system is, a poorly managed storage system can put your entire business at stake. You need a robust backup and storage architecture that gives you easy access or recover your complete set of data. This is where Zmanda can help.

Effective Storage Backup and Recovery With Zmanda

With this in mind, Zmanda has been designed for comprehensive storage, backup, and recovery for object and block storage. With Zmanda, you can replicate the backed-up data easily to an offsite location of your choice. Currently, the Zmanda backup engine supports the following types of object storage repositories for long-term data storage:

Try them out! Or if you are still torn between the type of architectural approaches as an ideal scalable storage solution, we have a hybrid/converged solution to fit your needs. Get in touch with us to understand how we leverage each solution while lowering your TCO (total cost of ownership) drastically.