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High performance storage management requires transferring large amounts of data and files within a network. Moving these files efficiently is especially useful for unstructured data types like large video files. With high performance storage, users can transfer at bit rates over one gigabyte per second, which can be particularly advantageous for businesses that regularly transfer petabytes of data.
A variety of high performance storage offerings are available to businesses looking to adopt cloud services. In this article, we’ll examine and discuss some popular options from the three major cloud providers: Amazon, Google, and Microsoft.
High performance storage systems (HPSS), initially developed by HPSS collaboration, allow for scalable storage management, archive, and file systems using various technologies. Through clustering, organizations can aggregate the individual capacities and performance of servers, computers, and drives to realize a significant performance boost.
Several methods exist for accessing data, including VFS (Linux), FTP, parallel FTP, and other client APIs. High performance storage is especially adept at managing active data. However, 60 to 90% of business data will become inactive within just months of creation. For optimal performance, this data should move off of HPSS.
Multiple methods of high performance storage options are available from a variety of vendors and offer an array of benefit. Here, we’ll discuss three primary storage systems: object, file, and block.
Object Storage
Amazon Web Services (AWS) offers object storage as its “simple storage service (S3)” with a variety of price points. Microsoft Azure provides object storage under the name of “Blob storage.” It has Premium, Hot, Cool, and Archive performance tiers with pay-as-you-go capabilities and volume discounts. Google cloud designates four performance tiers: Standard, Nearline, Coldline, and Archive. All services include versioning, encryption and fine-grained security with lifecycle management, archiving features and specific methods of handling infrequently accessed data.
File Storage
Azure offers file storage under the service name “files” with the same performance tiers as blob storage, including additional charges for metadata backup and optional snapshots. AWS’ Elastic File System (EFS) includes a managed petabyte-scale NFS service with multi-availability zone redundancy in Infrequent and Standard modes, as well as auto-tier options. Google cloud’s Filestore is another managed NFS service with three options tiers: HDD, SSD, and High-Scale SDD.
AWS features a unique file storage server: FSx for Windows or FSx for Lustre. This managed file service is used by applications that may need specific integration with storage servers. Several performance and redundancy configurations are available. Azure and Google Cloud currently have no comparable services.
Block Storage
Azure uses its “Azure managed disks” service for block storage. It is designed for VM attachment and has Ultra, Premium, and Standard SSD tiers with an additional HDD tier. Azure also has page blobs that are 512-byte long pages built for random read/write operations. They are available in SSD and HDD-based performance tiers. AWS outfits its elastic block service with a variety of IOPS at multiple latency levels. Google Cloud provides persistent disk block storage at eight different tiers—each with performance and reliability parameters, as well as zonal and regional options.
Because cloud service pricing can become complex, review each service’s price breakdown. Generally, Google Cloud offers the most affordable solution for object and file storage services, while Azure is the least expensive option for block storage. AWS places in the middle range for each storage type.
As outlined above, the three major cloud providers offer multiple high performance storage options. Before committing to a single provider, consider creating a detailed pricing model to better understand data storage in each of the three clouds.
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.
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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.