Google Cloud Platform (GCP) offers several storage options to meet different needs, including block storage, object storage, and file storage. [1]
Block storage divides data into evenly sized “blocks” and connects them to cloud compute instances for fast performance and low latency. Object storage manages data as flexible “objects” with metadata, making it highly scalable and durable. File storage enables access to data within a traditional hierarchical file system. [2]
This article compares GCP’s block storage, object storage, and file storage options across performance, scalability, use cases, and other factors.
Definition of Block Storage
Block storage refers to storage volumes that are mountable and provide raw block-level storage access to virtual machine instances. Block storage is used for databases, expandable file systems, or any applications requiring fine grain performance and control over storage. Google Cloud Persistent Disk provides block storage and is used by all virtual machine instances in Google Cloud Compute Engine.
Key characteristics of block storage include:
- Raw, block-level access to storage volumes
- Mountable as a file system or database storage
- Optimized for random reads/writes with low latency
- Delivers high performance for transactional workloads
Definition of Object Storage
Object storage is a data storage architecture that manages data as objects. Each object contains the data itself, some metadata, and an identifier. In object storage, the data is broken down into discrete units called objects that are stored in a flat structure instead of using a hierarchical file system.
Some key characteristics of object storage include:
- Data is stored as objects instead of files in a traditional file system.
- Each object contains the data, metadata describing the data, and a unique identifier.
- Objects are stored in a flat structure instead of a hierarchy.
- Object storage is designed to scale seamlessly, since it does not have the scaling limitations of a hierarchical file system.
- Object storage is ideal for storing unstructured data like images, videos, log files, backups, etc.
- Object storage systems are distributed geographically, allowing data to be stored globally.
Overall, object storage is optimized for storing huge volumes of unstructured data that needs to be accessible globally. It scales easily to meet storage demands.
Definition of File Storage
Google Cloud’s Filestore is a fully managed network file storage service for applications that require shared file storage and legacy applications relying on server message block (SMB) and network file system (NFS) protocols. File storage provides file-level access through POSIX and Windows interfaces, allowing applications to easily migrate from on-premises environments to the cloud.
Key characteristics of Google Cloud’s file storage include:
- Fully managed service that handles infrastructure maintenance and management
- High availability with replication across zones
- Integration with IAM for access controls
- Support for SMB and NFSv3 protocols to migrate legacy apps
- Scales up to 64 TB per file system
- Backed by SSD or HDD storage
- VMware certified to provide shared storage for GCP VMware Engine
Overall, Filestore provides fully managed file storage optimized for migrating legacy applications, running traditional fileworkloads, and integrating with VMware environments in Google Cloud.
Use Cases for Block Storage
Block storage in GCP is used for performance-sensitive workloads that require consistent, low-latency performance to deliver fast access to data. Major use cases for GCP block storage include:
According to this source, block storage is commonly used for databases, virtual machines, containers, analytics, gaming applications, and other high performance workloads. For example, block storage can provide fast read/write access for database management systems like MySQL, PostgreSQL, and MongoDB.
Block storage is also used for boot disks for GCP virtual machines, providing the root volume for the VM’s operating system. GCP’s Persistent Disks allow virtual machines to get consistent IOPS, throughput, and latency no matter the workload.
Additionally, block storage enables high performance for big data analytics tools like Apache Spark and Hadoop that require fast access to data. The consistent performance of block storage is critical for data pipelines and large-scale data processing.
Use Cases for Object Storage
Object storage is well-suited for storing unstructured data such as images, videos, audio files, documents, and more. Some major use cases for object storage include:
Backup and archival – Object storage can serve as a data repository for backups, archives, and data lakes. The scalability and resilience of object storage makes it useful for securely storing large amounts of unstructured data for long periods. Services like Cloud Storage provide object versioning for easily restoring previous versions.
Media storage and distribution – The high throughput and low latency of object storage can support workloads like audio and video streaming. Object storage can also accelerate content distribution from globally distributed edge locations.
Application data – Modern applications generate large amounts of unstructured data like user profiles, messages, timelines, etc. Object storage provides a flexible data store for cost-effectively managing this application data.
Static website hosting – Object storage buckets can host static websites and content very efficiently and inexpensively. Features like object versioning help manage changes.
Big data analytics – Object storage can collect, process, and analyze high volumes of unstructured data using services like Cloud Storage and BigQuery for insights.
Use Cases for File Storage
File storage in Google Cloud Platform (GCP) offers shared file systems that applications can connect to and use just like traditional on-premises file servers. Some major use cases for file storage on GCP include:
Lift-and-shift applications – Many legacy applications are built to use traditional file shares and cannot easily be refactored to use cloud object storage. File storage allows lifting those applications to the cloud without any code changes.
Migrating legacy systems – For organizations migrating legacy data centers and file servers to the cloud, file storage provides a familiar shared file system that eases the transition.
Shared file access – If multiple distributed applications, users, or servers need shared read/write access to files, file storage provides a centralized place to store files.
Local caching and batch processing – Applications that need low-latency access to file data can mount file shares locally and cache or batch process files efficiently.
Overall, the major use cases center around providing legacy compatibility, shared file access, and localized performance for applications transitioning to the cloud.
Comparing Performance
Google Cloud offers performance optimized or cost optimized storage options for block storage, object storage, and file storage. When comparing read/write speeds, IOPS, latency, and throughput it’s important to note the differences.
For block storage, SSD persistent disks offer up to 30,000 IOPS per VM instance with consistent low latency. Balanced persistent disks offer a maximum of 6,000 IOPS per VM. Standard persistent disks have lower IOPS limits and higher latency. SSDs provide the fastest performance for transactional workloads requiring consistent high IOPS.
Cloud Storage offers the highest throughput for large object uploads and downloads. As noted in this performance benchmark, multi-threaded uploads can fully saturate a gigabit connection. Latency and IOPS are lower compared to block storage.
Filestore provides lower latency than object storage using the NFS protocol, but does not match the IOPS potential of block storage disks. Throughput is dependent on the service tier selected. As documented, Filestore is ideal for lifting-and-shifting enterprise applications.
In summary, block storage offers the lowest latency and highest IOPS for transactional workloads. Object storage maximizes througput for large uploads/downloads. File storage fits in the middle for general purpose file workloads.
Comparing Scalability
When it comes to scalability, the three storage options offered by Google Cloud Platform (GCP) can scale to meet different needs:
Block storage volumes attached to Compute Engine virtual machine instances can scale up to 64 TB per volume as of 2022 according to Google’s documentation. So block storage offers high scalability on a per-volume basis. However, scaling to exabytes of block storage capacity would require managing a very high number of individual volumes.
Object storage via Cloud Storage is Google’s most scalable storage service, designed to scale from terabytes to exabytes seamlessly. According to Google’s scalability guide, Cloud Storage buckets can contain “unlimited storage” and handle “essentially unlimited throughput” when accessed over the internet. Google cites customers who store over 1 exabyte of data in Cloud Storage.
File storage via Cloud Filestore offers file server storage capacity between 1 TB to 64 TB per instance as of 2022. Multiple file server instances can be provisioned to achieve higher storage capacity. However, Cloud Filestore is better suited for scaling IOPS performance rather than massive storage capacity. According to Google’s limits, total capacity per project is limited to 2 PiB.
So in summary, object storage via Cloud Storage is designed to offer the most seamless scalability from terabytes to exabytes globally. Block storage and file storage have per-volume or per-instance limits that require deploying more resources to achieve petabyte-scale capacity.
Summary
Each storage option has its own strengths and use cases:
Block storage excels at providing fast performance for databases, transactional workloads, and boot disks. It offers consistent low latency and high throughput. Use block storage when you need raw storage volumes to mount directly into compute instances.
Object storage is ideal for cost-effectively storing large amounts of unstructured data like images, videos, backups, archives, and data lakes. It provides unlimited scalability and durability. Use object storage for data that does not require frequent updates or transactional processing.
File storage offers a simple way to migrate legacy applications to the cloud that rely on shared filesystems. It provides concurrent read/write access from multiple clients. Use file storage when you need a shared filesystem accessible via standard protocols like NFS and SMB.
The key is selecting the right storage type for your specific workload requirements and use case. Consider factors like performance needs, frequency of access, scalability, and cost.