Many of the most common workloads in today’s data center and cloud environments are read-dominant, as Figure 2 shows. These approximate workload characterizations are based on data collected worldwide across cloud and enterprise environments. The left side of the chart shows transfer sizes from 4KB through 1MB and up. The bottom of the chart shows a mixture of read/write, while the right side shows the data pattern from small/random to large/sequential.
Critical storage needs for the kinds of applications shown in Figure 3 are:
- Read-intensive storage that is still tunable
- High-capacity storage
- High-density storage
- Scalable storage
- Reliable storage
However, other needs involve power requirements and ease of service. In the past, the primary solution to such storage needs was hard disk drives (HDDs). But new solutions, including solid-state drives (SSDs), are emerging.
SSD alternatives to traditional HDDs
For many applications, an effective alternative to HDDs is QLC NAND SSDs. QLC stands for quad-level cells with 4 bits per cell, NAND are flash memory drives that do not require power to retain data, and SSD stands for solid-state drive.
1. QLC SSDs: Increased capacity and cost-effectiveness
QLC NAND SSDs, which work exceptionally well for read-intensive workloads, have significant data capacity, greater than single-level cell (SLC), multi-level cell (MLC), and triple-level cell (TLC) NAND SSDs. In addition, QLC NAND SSDs can compete with flash options that store fewer bits per cell, because they provide high-density storage while remaining economical.
2. QLC SSDs: Lower cost per gigabyte
Another advantage is that QLC NAND SSDs offer greater capacity in the same space at a lower cost per gigabyte. In addition to being low latency, they are highly reliable when compared with HDDs, [1] partly because QLC NAND SSDs do not have moving parts (unlike traditional HDDs).
When the focus is on storing data for the long term, QLC NAND SSDs provide an excellent option for data backup and archival purposes. For these applications, QLC NAND SSDs are a strong solution because of the need to balance performance, cost, and capacity.
Applications for QLC SSD
There are numerous and varied applications for QLC SSDs. Examples include machine learning (ML) and artificial intelligence (AI), where the drive primarily captures the data, which gets pulled from the drive while analytics are processed in a different workload.
Other applications that rely on QLC SSDs include OnLine Analytics Processing (OLAP), such as data mining for retail workloads, earthquakes, and high-performance computing (HPC). There are also Financial Service Industry (FSI) workloads, hyper-converged infrastructure (HCI), and CDNs.
These applications require rapid, high-bandwidth access to data and low-latency, read-optimized performance. A new product from Solidigm meets these intensive modern storage needs.
Solidigm QLC SSDs
The Solidigm D5-P5336 is a read performance-optimized storage solution for up to 61,44TB. As the value endurance QLC SSD option from Solidigm, the D5-P5336 offers high capacity at low total cost of ownership (TCO) for read-intensive workloads.
In supporting read-intensive storage, the D5-P5336 can read at 7,000 Mbps and write at 3,300 Mbps and is tunable with software to meet various workload needs more effectively. It has an excellent latency under load, a low error rate, and endurance on the order of 3,000 P/E cycles. [2]
- E3.5, covering a capacity range of 7.68TB to 30.72TB
- U.2, with a capacity range of 7.68TB to 61.44 TB
- E1.L, with capacities ranging from 15.35TB to 61.44TB
Revisiting Figure 2, Figure 3 shows where the Solidigm D5-P5336 provides optimal performance in read-dominant workloads.