2024.02.06

Introduction of storage options for AEWIN’s Platform

Share:

In a server/embedded platform environment, storage devices play a critical role in managing and providing access to vast amounts of data that servers need to store and retrieve. The selection of storage devices in a server setup is crucial for achieving optimal performance, reliability, and scalability. Here’s an introduction to common storage options in current standard AEWIN platforms.

Table1. Comparison of storage interfaces

Storage Interface SATA SAS NVMe
Form Factor 2.5”
mSATA
M.2
2.5” M.2
U.2
Data Transfer Rates SATA 3.0: 600 MB/s SAS 3.0: 12 Gbps
SAS4.0: 22.5 Gbps
PCIe3.0: 1 GB/s per lane
PCIe4.0: 2 GB/s per lane
Feature Cost-effective Reliability Low Latency
High Throughput
Excellent Scalability

 

There are three main interfaces/protocol of storages in AEWIN Server.

SATA, Serial ATA
Serial AT Attachment, SATA, is a computer bus interface that connects host bus adapters to mass storage devices. It is a widely used interface for connecting hard disk drives (HDDs) and solid-state drives (SSDs) to servers. It is a cost-effective solution suitable for most applications with moderate performance requirements. SATA interfaces are commonly found in servers and storage systems.

SAS, Serial Attached SCSI
Serial Attached SCSI, SAS, is a point-to-point serial protocol that transfer data to and from computer-storage devices. SAS error-recovery and error-reporting uses SCSI commands, which have more functionality than the ATA commands used by SATA drives. SAS is commonly used in mission-critical applications where speed and reliability are paramount.

NVMe, Non-Volatile Memory Express
Non-Volatile Memory Express or NVM Express, NVMe, is a storage interface specifically designed for modern, high-performance solid-state drives (SSDs). It is a protocol that leverages PCIe to provide direct communication between the storage device and the server’s CPU, reducing latency and improving overall performance.

Various kinds of form factors for each storage interfaces have been listed in table1 listed above. Each form factor has its own advantages and is suitable for specific use cases. For example, HDD is applied to achieve high capacity with the best TOC. As for mSATA and M.2, they are suitable for compact systems (further details of the dimension can be found in table2 below. U.2, with its compatibility with 2.5-inch bays, is often used in enterprise environments where high-performance, hot-swappable storage is essential.

Table2. Reference dimensions of storage devices with different form factors

Form Factor 2.5” 3.5” mSATA M.2 U.2
Length (mm) 100 147 50.8 80 100.35
Width (mm) 69.85 102 29.85 22 69.85
Height (mm) 7-15 26 4.85 3.5 7-15

 

Summary
As a Network Appliance provider, AEWIN designs platforms with great flexibility for installing a variety of the storage devices per customer’s requirements. Selected based on the features including speed/scalability/cost/dimension mentioned in this article, the most suitable storage options can be installed in AEWIN system for the best TCO.

Related News

Architecting Rack-Scale AI Infrastructure for the Neocloud Era
2026.09.24

Architecting Rack-Scale AI Infrastructure for the Neocloud Era

Generative and agentic AI applications, coupled with intensifying training and inference workloads, demand unprecedented compute throughput, memory, networking, and storage. Consequently, infrastructure can no longer be designed around isolated servers. The rise of specialized Neocloud providers further accelerates this shift toward rack-scale architecture, where compute, networking, and thermal management must converge to yield efficient, adaptable AI capacity.

Scalable Infrastructure for AI and Cloud-Native Applications
2026.09.09

Scalable Infrastructure for AI and Cloud-Native Applications

As AI adoption and cloud-native applications reshape enterprise IT, infrastructure must support increasingly diverse and dynamic workloads. From virtualization and distributed services to data-intensive applications, modern data centers require a balanced foundation of compute, memory, storage, and I/O performance. As workload demands continue to evolve, the infrastructure has to be built with superior scale and efficiency.

High-Density AI Infrastructure: Scaling Performance with Advanced Cooling Solutions
2026.09.02

High-Density AI Infrastructure: Scaling Performance with Advanced Cooling Solutions

As AI workloads demand greater processing power, data centers must achieve higher compute density and superior thermal efficiency while minimizing space and energy footprints. Integrating high-power CPUs and GPUs into compact server platforms makes advanced thermal management a critical factor in sustaining performance and optimizing infrastructure efficiency.

Inquiry Cart

total 0 items

Compare

total 0 items

Email Subscribe

Verification

Click the numbers from smallest to largest.

We use cookies to allow our website to work properly, personalize content and advertising, provide social media features and analyze traffic. We also share information about your use of our site with our social media, advertising and analytics partners

Manage Cookies

Privacy Settings

We use cookies to allow our website to work properly, personalize content and advertising, provide social media features and analyze traffic. We also share information about your use of our site with our social media, advertising and analytics partners

Privacy Policy

Manage Consent Settings

Essential Cookies

Accept All

The website cannot function without these cookies and you cannot switch them off on your system.

These cookies are typically set only in response to an action you perform (i.e. a service request), such as setting privacy preferences, logging in, or filling in a form.

You can set your browser to block or prompt you for these cookies, but this may prevent some site features from working.