Storage Media | Strengths | Use Cases |
NVME SSD local disks (only available for IO instances such as IT3 and IT5) | Low latency: provides microsecond-level access latency. | Acts as a temporary read cache: NVME SSD has excellent random read performance (4 KB/8 KB/16 KB random read) and is suitable for read-only slave databases for relational databases such as MySQL and Oracle. Since the cost of using memories is still higher than the cost of using SSDs, NVME SSD local disks can also be used as the secondary cache of Redis, Memcache, and other cache business. Note: NVME SSD carries the risk of a single point of failure. Therefore, we recommend that you implement data redundancy at the application layer to ensure reliability and use SSD cloud disks for your core business. |
SATA HDD local disk (only available for big data instances such as D2) | Provides the same data persistence as that of SSD at a fraction of the cost. It can be used as the cold data backup and the archive for important business, with a maximum capacity of 16 TB for a single disk. High throughput: provides the same throughput as those of local HDDs. | It is suitable for scenarios that involve the sequential reading and writing of large files, such as EMR and big data processing. |
Premium Cloud Storage | It is the most cost-effective option that is suitable for 90% of I/O scenarios. | It is suitable for small and medium databases, web servers, and other scenarios, and provides consistent and stable I/O performance. It meets the I/O demands for testing core business and developing joint testing environments. |
SSD | High performance and high data reliability: SSD uses the best-in-class NVMe solid state storage as the disk media. It is suitable for I/O-intensive business and provides long-term and ultra-excellent single disk performance. | Applicable use cases: Medium and large databases: supports medium and large relational database applications containing tables with millions of rows, such as MySQL, Oracle, and SQL Server. Core business systems: supports I/O-intensive applications and other core business systems with high data reliability requirements. Big data analysis: supports the distributed processing of TB- and PB-level data for data analysis, data mining, business intelligence, and other applications. |
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