Files, blocks, and objects are storage formats that hold, organize, and present data in different ways—each with their own capabilities and limitations. File storage organizes and represents data as a hierarchy of files in folders; block storage chunks data into arbitrarily organized, evenly sized volumes; and object storage manages data and links it to associated metadata.
Your organization’s data is one of its most valuable assets. Each piece of data or larger data sets — customer information, big data analytics, financial information, employee records, custom applications, etc. — requires you to make a crucial decision regarding where and how to store the information. While organizations often employ multiple types of storage, storage decisions should be made on the data level.
- Easy to modify
- Lack of metadata
- Not searchable
- High cost
- Email servers
- Virtual machine file system (VMFS) volumes
- Easy to access on a small scale
- Familiar to most users
- Users can manage their own files
- Allows access rights/file sharing/file locking to be set at user level
- Challenging to manage and retrieve large numbers of files
- Hard to work with unstructured data
- Becomes expensive at large scales
- Collaboration of documents
- Backup and recovery
- Handles large amounts of unstructured data
- Affordable consumption model
- Unlimited scalability
- Unlimited scalability
- Advanced search capabilities
- Cannot lock files
- Slower performance than other storage types
- Cannot modify a single portion of a file
- IoT data management
- Video surveillance
Block storage is when the data is split into fixed blocks of data and then stored separately with unique identifiers. The blocks can be stored in different environments, such as one block in Windows and the rest in Linux. When a user retrieves a block, the storage system reassembles the blocks into a single unit. Block storage is the default storage for both hard disk drive and frequently updated data. You can store blocks on Storage Area Networks (SANs) or in cloud storage environments.
Block storage chops data into blocks—get it?—and stores them as separate pieces. Each block of data is given a unique identifier, which allows a storage system to place the smaller pieces of data wherever is most convenient. That means that some data can be stored in a Linux environment and some can be stored in a Windows unit.
Block storage is often configured to decouple the data from the user’s environment and spread it across multiple environments that can better serve the data. And then, when data is requested, the underlying storage software reassembles the blocks of data from these environments and presents them back to the user. It is usually deployed in storage-area network (SAN) environments and must be tied to a functioning server.
Because block storage doesn’t rely on a single path to data—like file storage does—it can be retrieved quickly. Each block lives on its own and can be partitioned so it can be accessed in a different operating system, which gives the user complete freedom to configure their data. It’s an efficient and reliable way to store data and is easy to use and manage. It works well with enterprises performing big transactions and those that deploy huge databases, meaning the more data you need to store, the better off you’ll be with block storage.
There are some downsides, though. Block storage can be expensive. It has limited capability to handle metadata, which means it needs to be dealt with in the application or database level—adding another thing for a developer or systems administrator to worry about.
File storage is when all the data is saved together in a single file with a file extension type that’s determined by the application used to create the file or file type, such as .jpg, .docx or .txt. For example, when you save a document on a corporate network or your computer’s hard drive, you are using file storage. Files may also be stored on a network-attached storage (NAS) device. These devices are specific to file storage, making it a faster option than general network servers. Other examples of file storage devices include cloud-based file storage systems, network drives, computer hard drives and flash drives.
File storage uses a hierarchical structure where files are organized by the user in folders and subfolders, which makes it easier to find and manage files. To access a file, the user selects or enters the path for the file, which includes the sub-directories and file name. Most users manage file storage through a simple file system, such as File Manager.
File storage, also called file-level or file-based storage, is exactly what you think it might be: Data is stored as a single piece of information inside a folder, just like you’d organize pieces of paper inside a manila folder. When you need to access that piece of data, your computer needs to know the path to find it. (Beware—It can be a long, winding path.) Data stored in files is organized and retrieved using a limited amount of metadata that tells the computer exactly where the file itself is kept. It’s like a library card catalog for data files.
Think of a closet full of file cabinets. Every document is arranged in some type of logical hierarchy—by cabinet, by drawer, by folder, then by piece of paper. This is where the term hierarchical storage comes from, and this is file storage. It is the oldest and most widely used data storage system for direct and network-attached storage systems, and it’s one that you’ve probably been using for decades. Any time you access documents saved in files on your personal computer, you use file storage. File storage has broad capabilities and can store just about anything. It’s great for storing an array of complex files and is fairly fast for users to navigate.
The problem is, just like with your filing cabinet, that virtual drawer can only open so far. File-based storage systems must scale out by adding more systems, rather than scale up by adding more capacity.
Object storage is a system that divides data into separate, self-contained units that are re-stored in a flat environment, with all objects at the same level. There are no folders or sub-directories like those used with file storage. Additionally, object storage does not store all data together in a single file. Objects also contain metadata, which is information about the file that helps with processing and usability. Users can set the value for fixed-key metadata with object storage, or they can create both the key and value for custom metadata associated with an object.
Instead of using a file name and path to access an object, each object has a unique number. Objects can be stored locally on computer hard drives and cloud servers. However, unlike with file storage, you must use an Application Programming Interface (API) to access and manage object
Object storage, also known as object-based storage, is a flat structure in which files are broken into pieces and spread out among hardware. In object storage, the data is broken into discrete units called objects and is kept in a single repository, instead of being kept as files in folders or as blocks on servers.
Object storage volumes work as modular units: each is a self-contained repository that owns the data, a unique identifier that allows the object to be found over a distributed system, and the metadata that describes the data. That metadata is important and includes details like age, privacies/securities, and access contingencies. Object storage metadata can also be extremely detailed, and is capable of storing information on where a video was shot, what camera was used, and what actors are featured in each frame. To retrieve the data, the storage operating system uses the metadata and identifiers, which distributes the load better and lets administrators apply policies that perform more robust searches.
Object storage requires a simple HTTP application programming interface (API), which is used by most clients in all languages. Object storage is cost efficient: you only pay for what you use. It can scale easily, making it a great choice for public cloud storage. It’s a storage system well suited for static data, and its agility and flat nature means it can scale to extremely large quantities of data. The objects have enough information for an application to find the data quickly and are good at storing unstructured data.
There are drawbacks, to be sure. Objects can’t be modified—you have to write the object completely at once. Object storage also doesn’t work well with traditional databases, because writing objects is a slow process and writing an app to use an object storage API isn’t as simple as using file storage.
Stanley Ng (Stan) 黄宝明
Stan is a trainer, consultant, and coach for the past 15 years and has personally trained, consulted, and coached over 5,000 professionals from 45 fortune 500 companies. Stan is currently an active VMware Certified Instructor and Google Cloud Authorised Trainer delivering authorised IT trainings. Started his career as an IT engineer in 2005. By 2007, he led a team of 27 professionals from 5 countries managing large projects of over 10,000 users. From 2008 onwards, he started delivering training for fortune 500 companies.
- WSQ Advanced Certificate in Training & Assessment (ACTA)
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- VMware Certified Professional Cloud Management Automation (VCP-CMA)
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- Microsoft Certified Technology Specialist (MCTS) Hyper V
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