Block Storage vs. Object Storage vs. File Storage

Gurbir Singh

Jan 01, 2023 / 5 min read

Synopsys Cloud

Unlimited access to EDA software licenses on-demand

Your business's data is one of its most valuable assets. Regardless of the content of the data, whether it be financial information, applications, records, or something else, it necessitates taking the time to make intelligent decisions as to how best to store the information. Organizations generally use various storage types, each for their specific purposes. For this reason, it's important to be aware of the variety of storage types available —files, blocks, and object storage.

Each of the three storage types organizes and presents data in its own way. File storage organizes data within a hierarchy in folders, whereas block stages utilize arbitrarily organized storage chunks and evenly sized volumes. Object storage manages data and links to associated metadata, and we’ll be doing an in-depth discussion of each below.

What is File Storage?

File storage, also known as file-level or file-based storage, stores data as single pieces of information inside folders. When the data needs to be accessed, the user can go down the path to find it. Data in files are organized using a limited amount of metadata that tells the computer where the file is kept.

You can think of file storage as a closet with cabinets and each document arranged logically. This file storage system is the oldest and most widely used, and likely the one that is most familiar to users, as when accessing data on your personal computer, file storage is used. File storage has a range of capabilities and can store nearly anything. Common use cases include collaborating on documents, backup and recovery, and archival purposes.

In file storage systems, the data is saved in a single file in an extension type determined by the application (e.g., .jpg, .docx, .txt). File storage is easy to access on a small scale and is most appropriate with a small-to-moderate number of files: users can easily navigate down the file path to find their desired file. This also allows access rights, file locking, and file sharing at the user level. Files can be set as read-only, locked, or written, in addition to being password protected.

File-based storage systems must scale out by adding additional systems rather than scaled up by adding capacity. Furthermore, it becomes challenging to manage and retrieve large numbers of files as the number of folders and subfolders increases. It also makes it difficult to work with unstructured data such as text, mobile activity, and IoT sensor data — especially in large amounts. When storage space reaches capacity, additional hardware must be purchased, making it difficult to manage at large scales.

What is Block Storage?

As the name suggests, block storage stores data in blocks and as separate pieces. Each block has a unique identifier (UID), which allows storage systems to place the smaller pieces of data in the most convenient places. Block storage is often set up to decouple the data from the user’s environment and spread it across various environments that can more easily handle it. Once the data is requested, the storage system reassembles it and returns it to the user.

As block storage doesn’t utilize a single path to data (like file storage), it can be retrieved more rapidly. Every block is self-contained and can be placed to be accessed in various operating systems, giving the user complete control for configuring the data. It is an efficient and reliable method to store data and is simple to use and manage.

Especially useful for enterprises with large transactions and massive databases, the more data an organization has, the better block storage is suited for them. Block storage generally has high performance with low latency and retrieval. Modification is easy as all that is required is a new version to be created rather than creating a new block. Block storage is often used for transactional databases, email servers, and virtual machine file systems due to its high-performance capability.

Block storage is rather expensive and cannot handle metadata or object storage. Therefore, metadata must be dealt with at the database or application level, adding additional complexity. Large volumes of block data may become unmanageable, as block storage has limited search capabilities. Additionally, purchasing more block storage may be expensive, especially at high scales.

What is Object Storage?

Object-based storage utilizes a flat structure where files are broken into discrete pieces called objects and spread out among hardware. Data is kept in a single repository rather than folders or blocks on servers, as with the other storage types. Not all data is stored together in a single file. Storage volumes for objects are modular. Each piece is a self-contained repository that owns the data, a UID for searching over a distributed system, and metadata describing the data, with information such as security, access contingencies, and age.

For data retrieval, the system uses metadata and UIDs, which distributes the load better and allows administrators to apply policies and robust searches. Unlike file storage, an API is required to access and manage objects.  Object storage use cases include IoT data management, backup and recovery, email storage, and video surveillance.

Object storage is cost-efficient as you only pay for what you use. Scaling is easy, and it’s especially suited for static data. Its agility and flat nature allow it to scale to extremely large quantities of data, in addition to being especially suited for unstructured data. Since metadata is stored with objects, users can gain value from this information and easily retrieve any objects they need. Object storage enables advanced search capabilities through metadata, object contents, and other properties.

Drawbacks include that objects cannot be modified and have to be written entirely at once. Object storage is also more challenging to incorporate into traditional databases as creating objects is relatively slow, and creating an app to use object storage API isn’t as straightforward as file storage. You cannot lock files, and performance may be slower than other storage types.

Which is Right for your Organization?

When choosing the right storage for you, consider the type of data your organization will intend to store. Furthermore, as costs involved with block and file storage are greater, choose based on the amount of data you intend to store. Each type of storage is best for different workflows, and by understanding your organization's specific organizational, security, and data needs, you can select the type(s) that are most suitable for your purposes.

Synopsys, EDA, and the Cloud

Synopsys is the industry’s largest provider of electronic design automation (EDA) technology used in the design and verification of semiconductor devices, or chips. With Synopsys Cloud, we’re taking EDA to new heights, combining the availability of advanced compute and storage infrastructure with unlimited access to EDA software licenses on-demand so you can focus on what you do best – designing chips, faster. Delivering cloud-native EDA tools and pre-optimized hardware platforms, an extremely flexible business model, and a modern customer experience, Synopsys has reimagined the future of chip design on the cloud, without disrupting proven workflows.

 

Take a Test Drive!

Synopsys technology drives innovations that change how people work and play using high-performance silicon chips. Let Synopsys power your innovation journey with cloud-based EDA tools. Sign up to try Synopsys Cloud for free!


About The Author

Gurbir Singh is group director, Cloud Engineering, at Synopsys. He has a demonstrated history of leadership in the software industry. In his current role, he leads the development of the Synopsys Cloud product, which enables customers to do chip design on the cloud using EDA-as-a-Service (SaaS) as well as flexible pay-per-use models. Gurbir has run organizations to develop cloud SaaS products, machine learning applications, AI/ML platforms, enterprise web applications, and high-end customer applications. He is experienced in building world- class technology teams. Gurbir has a master’s degree in computer science, along with patents and contributions to publications.

Continue Reading