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Kingston’s new DC3000ME is the latest enterprise-class NVMe SSD featuring a U.2 2.5″ form factor, specifically crafted for data center and server-grade workloads. Leveraging the PCIe 5.0 x4 interface, it combines high-bandwidth throughput with 3D eTLC NAND, ensuring robust reliability and flexible capacity scaling. Offered in 3.84TB, 7.68TB, and 15.36TB configurations, this drive is tailored for high-demand environments, including hyperscale infrastructure, AI and HPC clusters, cloud services, and transactional systems.
Kingston DC3000ME Performance Profile
Across all capacity options, the DC3000ME maintains consistent sequential read performance, with each model delivering up to 14,000MB/s. This speed is perfect for workloads dependent on fast data access, no matter the selected capacity. In contrast, sequential write speeds differ noticeably: the 3.84TB model tops out at 5,800MB/s, the 7.68TB variant jumps to 10,000MB/s, and the 15.36TB model slightly lags at 9,700MB/s.
In terms of random performance, the 7.68TB model stands out as the fastest, boasting a maximum of 2.8 million IOPS for reads and 500,000 IOPS for writes. This outperforms both the 3.84TB and 15.36TB drives, which are limited to 2.7 million IOPS for reads. For writes, the 3.84TB model reaches 300,000 IOPS, while the 15.36TB model hits 400,000 IOPS. Overall, the 7.68TB version is the most capable of handling busy, high-demand tasks.
From a performance-per-capacity perspective, the 7.68TB model also offers the most balanced mix of throughput and IOPS, making it ideal for write-intensive applications like logging, OLTP databases, or active AI model training. The 3.84TB model is better suited for read-heavy or mixed workloads where capacity is not a top priority, while the 15.36TB version sacrifices peak write IOPS for raw storage density.
Kingston DC3000ME Enterprise Features
The DC3000ME comes equipped with practical enterprise-grade features essential for production systems. It includes power-loss protection (PLP) to safeguard data in case of sudden outages, as well as AES-256 encryption with TCG Opal support for secure data at rest. The drive supports up to 128 namespaces, a feature particularly useful for virtualized or containerized environments—matching the capabilities of advanced U.2 SSDs and adding value for large-scale virtualization. Kingston has also integrated telemetry tools to monitor drive health, media wear, and operating temperature, giving administrators clear visibility into long-term reliability.
Kingston DC3000ME back
Power consumption ranges from 8W at idle to a maximum of 24W during full write operations, which is standard for dense U.2 SSDs under heavy load. Kingston specifies a maximum read power of 8.2W, closely aligning with the idle power draw and resulting in a narrow power difference under read-heavy workloads. Endurance ratings meet enterprise standards, supporting one full drive write per day over a five-year period—equating to 7,008TBW to 28,032TBW, depending on the drive’s capacity.
The Kingston DC3000ME is backed by a two-million-hour MTBF rating, Kingston’s five-year limited warranty, and complimentary technical support.
Kingston DC3000ME Specifications
| Specification | Details |
| Form Factor | U.2, 2.5″ x 15mm |
| Interface | PCIe NVMe Gen5 x4 (backward-compatible with Gen4) |
| Capacities | 3.84TB, 7.68TB, 15.36TB |
| NAND Type | 3D eTLC NAND |
| Sequential Read/Write (MB/s) | 3.84TB – 14,000 / 5,800 7.68TB – 14,000 / 10,000 15.36TB – 14,000 / 9,700 |
| Random Read/Write IOPS (4K) | 3.84TB – 2,700,000 / 300,000 7.68TB – 2,800,000 / 500,000 15.36TB – 2,700,000 / 400,000 |
| Latency QoS (99%) | Read: <10µs, Write: <70µs |
| Static and Dynamic Wear Leveling | Yes |
| Power Loss Protection | Yes (Power Caps) |
| Encryption | TCG Opal 2.0, AES 256-bit encryption |
| Namespace Management | Up to 128 namespaces supported |
| Enterprise Diagnostics | Telemetry, media wear, temperature, health, etc. |
| Endurance (TBW / DWPD, 5 Years) | 3.84TB – 7,008 TBW, 1 DWPD 7.68TB – 14,016 TBW, 1 DWPD 15.36TB – 28,032 TBW, 1 DWPD |
| Power Consumption | Idle: 8W, Max Read: 8.2W, Max Write: 24W |
| Operating Temperature | 0°C to 70°C |
| Dimensions | 100.50mm x 69.8mm x 14.8mm |
| Weight | 3.84TB – 146.2g 7.68TB – 151.3g 15.36TB – 152.3g |
| Vibration (Non-Operating) | 10G Peak (10–1000Hz) |
| MTBF | 2 million hours |
| Warranty and Support | 5-year limited warranty with free technical support |
Kingston DC3000ME Performance Testing
Drive Testing Platform
We utilize a Dell PowerEdge R760 running Ubuntu 22.04.02 LTS as our test platform for all workloads in this review. Equipped with a Serial Cables Gen5 JBOF, it offers wide compatibility with U.2, E1.S, E3.S, and M.2 SSDs. Our system configuration is outlined below:
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- 2 x Intel Xeon Gold 6430 (32-Core, 2.1GHz)
- 16 x 64GB DDR5-4400
- 480GB Dell BOSS SSD
- Serial Cables Gen5 JBOF
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Drives Compared
CDN Performance
To simulate a realistic, mixed-content CDN workload, the SSDs underwent a multi-phase benchmark sequence designed to replicate the I/O patterns of content-heavy edge servers. The testing process covers a range of block sizes—both large and small—distributed across random and sequential operations, with varying concurrency levels.
Prior to the main performance tests, each SSD completed a full device fill via a 100% sequential write pass using 1MB blocks. This process employed synchronous I/O and a queue depth of four, enabling four simultaneous jobs. This phase ensures the drive enters a steady-state condition that mirrors real-world usage. Following the sequential fill, a secondary three-hour randomized write saturation stage was run, using a weighted block size distribution (block size/percentage) with a strong focus on 128K transfers (98.51%), supplemented by minor contributions from sub-128K blocks down to 8K. This step emulates the fragmented, uneven write patterns commonly seen in distributed cache environments.
The main testing suite focused on scaled random read and write operations to measure the drive’s performance under variable queue depths and job concurrency. Each test ran for five minutes (300 seconds), followed by a three-minute idle period to allow internal recovery mechanisms to stabilize performance metrics.
Testing was conducted using a fixed block size distribution favoring 128K (98.51%), with the remaining 1.49% of operations consisting of smaller transfer sizes ranging from 64K to 8K. Each configuration varied across 1, 2, and 4 concurrent jobs, with queue depths of 1, 2, 4, 8, 16, and 32, to profile throughput scalability and latency under typical edge-write conditions.
A heavily mixed block size profile, mimicking CDN content retrieval, was also used—starting with a dominant 128K (83.21%) component, followed by a long tail of over 30 smaller block sizes (4K to 124K), each with fractional frequency representation. This distribution reflects the diverse request patterns encountered during video segment fetching, thumbnail access, and metadata lookups. These tests were also run across the full matrix of job counts and queue depths.
This combination of preconditioning, saturation, and mixed-size randomized access tests is designed to reveal how SSDs perform in sustained CDN-like environments, emphasizing responsiveness and efficiency in bandwidth-heavy, highly parallelized scenarios.
CDN Workload Read 1
In our CDN workload read tests (1 job), the Kingston DC3000ME delivered solid performance that scaled effectively with increasing queue depth. At QD1, it achieved 940MB/s, trailing the SanDisk SN861 by approximately 26%. However, as queue depth increased, the DC3000ME narrowed the gap and outperformed several Gen5 drives. At QD4, the Kingston DC3000ME reached 3,390MB/s—roughly 42% faster than the Micron 9550, 40% ahead of the Pascari X200P, and about 25% faster than the Solidigm PS1010, though slightly behind the SanDisk SN861 by around 2.6%. At QD16, the DC3000ME hit 9,645MB/s, surpassing the Solidigm PS1010 by ~13% and the Micron 9550 by ~20%. At the maximum test depth of QD32, Kingston achieved 14,131MB/s, effectively matching the Micron 9550 and outperforming the Solidigm PS1010 by ~15% and the SanDisk SN861 by nearly 10%.
Kingston DC3000ME - CDN Workload Read 1 job
CDN Workload Read 2
In the 2-job CDN read workload, the Kingston DC3000ME maintained strong performance across all queue depths. At QD1, it posted 1,854MB/s—faster than the Micron 9550 (1,548MB/s) by 20%, the Pascari X200P (1,519MB/s) by 22%, and the Solidigm PS1010 (2,011MB/s) by approximately 8%, though trailing the SanDisk SN861 (2,487MB/s) by 34%.
At QD4, Kingston reached 6,335MB/s, noticeably outperforming the Micron (5,337MB/s), Pascari (5,249MB/s), and Solidigm (5,609MB/s). However, it still lagged behind SanDisk, which took the top spot at 6,996MB/s.
By QD16, Kingston hit 14,131MB/s, leading the pack at this point. At the final test point (QD32), it achieved a slight increase to 14,336MB/s—trailing Pascari (15,257MB/s) and Micron (15,052MB/s) by ~6% and 5%, respectively, while maintaining a solid lead over SanDisk (13,619MB/s) and Solidigm (13,721MB/s).
CDN Workload Read 4
With four jobs active, the Kingston DC3000ME continued to hold its own in CDN read performance. At QD1, it reached 3,639MB/s—outperforming the Micron 9550 (3,070MB/s) and Pascari X200P (2,982MB/s), but still 22% behind the SanDisk SN861, which led this tier at 4,443MB/s. By QD4, Kingston delivered 10,854MB/s—a 15% improvement over Micron (9,427MB/s), 20% ahead of Pascari (9,070MB/s), and slightly above Solidigm (9,627MB/s). However, it still trailed SanDisk’s 11,161MB/s.
By QD8, Kingston posted 13,926MB/s—almost identical to Micron and roughly in line with SanDisk (13,619MB/s) and Solidigm (12,800MB/s). At QD16 and QD32, throughput plateaued around 14,131–14,233MB/s for Kingston, slightly behind Micron and Pascari (both around 15,052–15,257MB/s), but still comfortably ahead of SanDisk (13,619MB/s) and Solidigm (13,721MB/s).
CDN Workload Write 1
In our CDN write workload (1 Job), the Kingston DC3000ME showed consistent scaling across queue depths. At QD1, it reached 2,118MB/s—faster than the Micron 9550 (2,004MB/s), Pascari X200P (1,885MB/s), and Solidigm PS1010 (1,718MB/s), while trailing the SanDisk SN861 by just a hair (2,164MB/s). At QD4, Kingston posted 4,318MB/s—55% faster than Solidigm (2,789MB/s), 26% faster than Pascari (3,437MB/s), but 10% slower than Micron (4,807MB/s) and 19% behind SanDisk (5,353MB/s).
By QD16, it delivered 5,880MB/s—edging out Pascari (4,921MB/s) by 20% and more than doubling Solidigm (2,664MB/s), but still 11% behind Micron (6,686MB/s) and 15% off SanDisk (6,939MB/s). At QD32, Kingston capped at 5,987MB/s—again close to Pascari (5,913MB/s), but trailing Micron (7,422MB/s) and SanDisk (7,521MB/s) by ~20% and 25%, respectively.
Kingston DC3000ME - Write performance CDN workload 1 job
CDN Workload Write 2
In the 2-job CDN write workload, the Kingston DC3000ME demonstrated consistent performance, though it generally trailed the fastest Gen5 enterprise-class SSDs. At QD1, it posted 2,651MB/s—just under the Micron 9550 (2,813MB/s) and Pascari X200P (2,762MB/s), and about 33% behind the SanDisk SN861 (3,972MB/s).
As queue depth increased, the DC3000ME kept pace. At QD4, it reached 4,807MB/s—about 23% slower than the Micron 9550 (5,902MB/s) and 13% behind the SanDisk SN861 (5,508MB/s), but ahead of the Solidigm PS1010 at 3,154MB/s.
At QD16, Kingston delivered 5,772MB/s—still trailing Micron (7,896MB/s) and SanDisk (6,709MB/s), but continuing to outperform lower-tier models like the Solidigm PS1010 (3,820MB/s) and Pascari X200P (5,417MB/s). At QD32, the DC3000ME peaked at 5,870MB/s—about 32% behind the Micron 9550 (8,670MB/s) and 22% below the SanDisk SN861 (7,537MB/s), but still ahead of the Solidigm PS1010 (2,817MB/s) and Pascari (4,585MB/s).
CDN Workload Write 4
In the 4-job CDN write workload, the Kingston DC3000ME scaled steadily across all queue depths, though it generally trailed the top two Gen5 drives. At QD1, it achieved 2,202MB/s—placing it behind the Pascari X200P (2,845MB/s), Micron 9550 (2,703MB/s), and SanDisk SN861 (3,544MB/s), but ahead of the Solidigm PS1010 (2,020MB/s). At QD2, Kingston reached 3,165MB/s—again lagging behind SanDisk (4,863MB/s) and Micron (4,457MB/s), but maintaining a lead over Solidigm (2,872MB/s).
At mid-range queue depths, the Kingston DC3000ME achieved 3,647MB/s at QD4 and 4,410MB/s at QD8. While this showed decent scaling, it remained behind the Micron drive (5,539MB/s and 6,478MB/s) and SanDisk drive (5,177MB/s and 5,575MB/s) at both test points. At QD16, Kingston delivered 4,865MB/s—a modest gain over QD8 but still trailing the SanDisk drive (6,011MB/s) and Micron drive (7,474MB/s). At QD32, the DC3000ME reached its peak at 5,307MB/s—holding well ahead of Solidigm (3,894MB/s) but significantly behind Micron (7,941MB/s) and SanDisk (7,212MB/s). While not a performance leader, the Kingston drive maintained consistent scaling and efficiency.
DLIO Checkpointing Benchmark
To evaluate SSD real-world performance in AI training environments, we used the Data and Learning Input/Output (DLIO) benchmark tool. Developed by Argonne National Laboratory, DLIO is specifically designed to test I/O patterns in deep learning workloads, providing insights into how storage systems handle challenges like checkpointing, data ingestion, and model training. The chart below illustrates how both drives handle the process across 36 checkpoints. When training machine learning models, checkpoints are critical for saving the model’s state periodically, preventing progress loss during interruptions or power failures. This storage demand requires robust performance, especially under sustained or intensive workloads. We used DLIO benchmark version 2.0 from the August 13, 2024, release.
To ensure our benchmarking reflected real-world scenarios, we based our testing on the LLAMA 3.1 405B model architecture. We implemented checkpointing using torch.save() to capture model parameters, optimizer states, and layer states. Our setup simulated an eight-GPU system, using a hybrid parallelism strategy with 4-way tensor parallelism and 2-way pipeline parallel processing distributed across the eight GPUs. This configuration resulted in checkpoint sizes of 1,636GB—representative of modern large language model training requirements.
In the DLIO average pass results, the Kingston DC3000ME 7.68TB trailed slightly behind top contenders, landing in the middle of the five-drive pack. Checkpoint times averaged 465.04 seconds in the first pass, 584.38 seconds in the second pass, and 590.30 seconds in the third pass. While consistently quicker than the Pascari X200P 7.68TB (which posted the highest times across all three passes, reaching 674.48 seconds in pass 3), the Kingston DC3000ME lagged the Micron 9550 7.68TB and Solidigm PS1010 7.68TB—both of which remained below 565 seconds in the final pass.
As shown in the chart below, the Kingston DC3000ME got off to a strong start, with early checkpoint times closely matching those of top-tier competitors. At checkpoint 1, it posted 469.27 seconds—just behind the Micron 9550 at 464.01 seconds and ahead of the Pascari X200P at 472.65 seconds. From checkpoint 2 through 4, it maintained a steady range of 461.92 to 465.44 seconds—again staying close to the Micron 9550 and Solidigm PS1010, both of which hovered in the 453–465 second bracket.
By the middle of the test (checkpoints 5 to 8), the Kingston DC3000ME experienced a jump in checkpoint times, peaking at 613.01 seconds during checkpoint 7. This was higher than the Micron 9550 (570.42s) and SanDisk SN861 7.68TB (559.56s), though still significantly better than the Pascari X200P (which reached as high as 694.38 seconds during the same interval). Toward the end of the test, the Kingston DC3000ME stabilized slightly, finishing at 571.36 seconds for checkpoint 12—roughly 28 seconds slower than the Micron 9550 but still outpacing the Pascari X200P (which closed at 689.68 seconds). Overall, the Kingston DC3000ME 7.68TB demonstrated consistent performance and remained within a competitive range throughout the checkpointing workload, placing it in the middle of the pack.
FIO Performance Benchmark
To measure the storage performance of each SSD across common industry metrics, we used FIO. Each drive underwent the same testing process, including a preconditioning step of two full drive fills with a sequential write workload, followed by steady-state performance measurement. As each workload type changed, we ran another preconditioning fill of that new transfer size.
In this section, we focus on the following FIO benchmarks:
-128K Sequential
-64K Random
-16K Random
-4K Random
With high-capacity QLC SSDs designed for large transfer sizes, our write speed tests are limited to 16K random. For 4K, we used the pre-filled state from the 16K workload to measure only 4K random read performance.
128K Sequential Precondition (IODepth 256 / NumJobs 1)
In this heavy queue-depth preconditioning test, the Kingston DC3000ME maintained a steady write bandwidth of 8,944.9MB/s throughout the 1,000-second run (finishing just past the 800-second mark). While not the fastest (trailing slightly behind the Micron 9550, which peaked at 10.3GB/s), the Kingston DC3000ME demonstrated consistent throughput with minimal variance.
128K Sequential Precondition Latency (IODepth 256 / NumJobs 1)
In the 128K Sequential Write Precondition latency test, the Kingston DC3000ME showed an average latency of 3.577ms (remaining stable over time with minimal fluctuation), placing it second behind the Micron drive.
128K Sequential Write (IODepth 16 / NumJobs 1)
In the 128K Sequential Write Test, the Kingston DC3000ME achieved 8,477.4MB/s—placing it just behind the Micron 9550 (which led the group at 10,354.6MB/s). The Kingston DC3000ME outperformed the Pascari X200P and maintained a solid lead over both the Solidigm PS1010 and SanDisk SN861 (each hovering around 7,100MB/s). Kingston’s performance reflects a strong balance between speed and consistency.
128K Sequential Write Latency (IODepth 16 / NumJobs 1)
In the 128K Sequential Write Latency test, the Kingston DC3000ME delivered a solid result with an average latency of 235.6µs. This places it ahead of both the SanDisk SN861 (280.7µs) and Solidigm PS1010 (280.3µs), while slightly edging out the Pascari X200P (238.6µs). Though not quite as fast as the Micron 9550 (which led at 192.9µs), the Kingston DC3000ME remained competitive.
128K Sequential Read (IODepth 64 / NumJobs 1)
In the 128K Sequential Read test at a queue depth of 64 with one job, the Kingston DC3000ME achieved 13,513.8MB/s. Though placing fourth among tested drives, it still delivered strong throughput (with minimal real-world differences). It trailed the Pascari X200P (14,242.1MB/s) by ~5.1%, the Solidigm PS1010 (14,163.3MB/s) by 4.6%, and the Micron 9550 (14,050.1MB/s) by ~3.8%, but comfortably outperformed the SanDisk SN861 (12,631.2MB/s). Overall, the Kingston DC3000ME’s results were strong, with minimal drop-off compared to top-tested drives.
128K Sequential Read Latency (IODepth 64 / NumJobs 1)
For latency, the Kingston DC3000ME recorded an average of 591.6µs—placing it in the middle of the group. This result was 5.4% higher than the Micron 9550 (569.0µs) and 5.4% lower than the Solidigm PS1010 (564.5µs). The Pascari X200P led marginally at 561.4µs, while the SanDisk SN861 showed the slowest response at 633.0µs. Ultimately, the Kingston DC3000ME maintained relatively low latency under high queue depth read conditions.
64K Random Write
In the 64K Random Write test, the Kingston DC3000ME consistently delivered high performance across various queue depths and thread combinations, peaking at 6,649MB/s in the 32 (IO depth)/8 (numjobs) configuration—among the highest across all workloads and test points.
Throughout the chart, the Kingston DC3000ME maintained a stable bandwidth trend of 4,000 to 5,000MB/s, with particularly strong showings in mid-to-high concurrency setups (e.g., 32/4 at 5,380MB/s and 16/8 at 5,017MB/s). Even under lighter conditions (1/4 and 2/4), it maintained above 4,200MB/s. Compared to other drives, the Kingston DC3000ME generally led or remained near the top across most test points, offering both high peak throughput and consistent performance.
64K Random Write Latency
In the 64K Random Write Latency test, the Kingston DC3000ME consistently delivered low response times across most queue depths and job combinations, demonstrating strong write efficiency even under heavy load.
For example:
- At 4/1, it showed 49µs
- At 8/1, latency stayed low at 102µs
- At 16/4, it measured 1,486µs
- And at the highest tested load, 32/8, it reached 2,402µs
These results indicate the Kingston DC3000ME scaled predictably, avoiding the severe latency spikes seen in other drives—especially the Pascari and Solidigm models, which exhibited erratic jumps above 3,000–6,000µs (most notably at 16/8).
64K Random Read
In the 64K Random Read test, the Kingston DC3000ME delivered strong, consistent performance across the entire IOdepth/NumJobs matrix, finishing fourth by the end of the test (by a small margin). Peak bandwidth reached 13,515MB/s at 32/4, with similarly high throughput at 16/4 (13,482MB/s) and 32/8 (13,512MB/s)—demonstrating excellent scalability under heavy parallel read workloads. At lower loads (1/4 and 2/2), the Kingston DC3000ME measured 2,298MB/s and 2,234MB/s, respectively.
64K Random Read Latency
The Kingston DC3000ME’s 64K latency remained relatively low across all test points. All drives performed similarly, though the SanDisk SN861 peaked noticeably higher than others at the end of the test. Starting at 1/2, the Kingston DC3000ME measured 106µs, followed by 108µs at 1/4, 131µs at 8/1, 133µs at 4/4, and 177µs at 8/4. At higher concurrency, it increased to 305µs at 16/4, 174µs at 32/1, 301µs at 32/2, and peaked at 1,184µs under 32/8—aligning with the rest of the group. Overall, the Kingston DC3000ME’s latency profile tracked closely with top performers, with minimal jitter or outlier spikes (common to all tested drives).
16K Random Write
In the 16K Random Write test, the Kingston DC3000ME delivered strong bandwidth across the full range of queue depths and thread counts, finishing second among competing drives. It topped out at 427,592 IOPS under the 32/16 configuration. Other high-performing points included 338,521 IOPS at 32/8, 251,428 IOPS at 16/4, and 226,606 IOPS at 1/8—all showing excellent controller efficiency under varying parallel loads. Even in moderate load setups (2/16 and 1/4), the drive achieved 218,300 IOPS and 204,867 IOPS, respectively. Overall, the Kingston DC3000ME consistently achieved IOPS above 160,000 across the test matrix (except in a few areas), making it one of the more balanced drives in this workload.
16K Random Write Latency
The Kingston DC3000ME’s 16K write latency performance was excellent, finishing at the top of the leaderboard (with the Pascari drive trailing slightly). Highlights included 14µs at 1/1, 18µs at 2/1, 19µs at 1/4, and 29µs at 1/2. As load increased, Kingston maintained a strong latency profile: 126µs at 8/4, 146µs at 2/16, 254µs at 16/4, and 575µs at 16/8. Even at the heaviest configuration (32/16), latency remained controlled at 1,197µs.
16K Random Read
Under 16K random read conditions, the Kingston DC3000ME demonstrated consistently strong performance until reaching 8/8, at which point it began to fall behind slightly. Peak IOPS landed at just under 800K (648,686) at QD32 with four jobs, followed by 641K IOPS at QD4 with 16 jobs and 623K at QD16 with four jobs. Unfortunately, the Kingston DC3000ME finished near the bottom of the leaderboard alongside the SanDisk drive.
16K Random Read Latency
At peak throughput (QD8/8), the Kingston DC3000ME’s latency measured just 99µs, staying within a narrow, low-latency band across most configurations until around 16/8, when it started to falter. The best latency was observed at QD1/4 (74µs), with several other sub-80µs results at low to moderate queue depths. At heavier loads (e.g., QD32/16), the Kingston DC3000ME posted 826µs—significantly higher than other tested drives (except SanDisk).
4K Random Read
In the 4K random read test, the Kingston DC3000ME showed excellent scaling across the test range, peaking at 1,957.92K IOPS under the 16/16 configuration. It maintained high throughput at 1,923.42K IOPS at 32/8, 1,361.32K IOPS at 8/16, and 1,326.03K IOPS at 16/8—consistently ranking at the top of the leaderboard alongside Solidigm and Micron.
4K Random Read Latency
The Kingston DC3000ME maintained low latency throughout the 4K random read test, starting at 60µs under the 1/1 configuration. At 1/4, it improved slightly to 61µs, and at 1/8, it remained steady at 63µs. As concurrency increased, latency scaled predictably: 66µs at 2/4, 67µs at 2/16, 71µs at 4/4, and 80µs at 8/4. Heavier configurations saw modest rises: 94µs at 16/4, 99µs at 16/8, 135µs at 32/8, and a peak of 266µs at 32/16.
4K Random Write
In 4K random write, the Kingston DC3000ME delivered a strong showing with a maximum of 979,636 IOPS at 32/16 and 979,173 IOPS at 32/8—placing it well behind the top performer (Pascari X200P, which exceeded 1.6M IOPS at peak). That said, the Kingston DC3000ME posted decent numbers in midrange loads: 879K IOPS at 8/16, 944K IOPS at 16/16, and 745K IOPS at 16/4.
4K Random Write LatencyIn random write latency, the Kingston DC3000ME started at 11µs under 1/1, stayed around 20–50µs until hitting the 8/8 depth, and scaled to 261µs at 32/8 and 522µs at 32/16. While not the lowest in latency, the Kingston DC3000ME maintained predictable, moderate scaling—without the spikes seen in drives like Solidigm and Pascari, which showed greater volatility beyond 16 threads.
GPU Direct Storage
One of the tests we conducted on this testbench was the Magnum IO GPU Direct Storage (GDS) test. GDS is a feature developed by NVIDIA that allows GPUs to bypass the CPU when accessing data stored on NVMe drives or other high-speed storage devices. Instead of routing data through the CPU and system memory, GDS enables direct communication between the GPU and storage device—significantly reducing latency and improving data throughput.
How GPU Direct Storage Works
Traditionally, when a GPU processes data stored on an NVMe drive, the data must first travel through the CPU and system memory before reaching the GPU. This process introduces bottlenecks, as the CPU acts as a middleman—adding latency and consuming valuable system resources. GPU Direct Storage eliminates this inefficiency by enabling the GPU to access data directly from the storage device via the PCIe bus. This direct path reduces data movement overhead, allowing faster, more efficient transfers.
AI workloads—especially deep learning—are highly data-intensive. Training large neural networks requires processing terabytes of data, and any delay in data transfer can lead to underutilized GPUs and longer training times. GPU Direct Storage addresses this challenge by ensuring data is delivered to the GPU as quickly as possible, minimizing idle time and maximizing computational efficiency.
Additionally, GDS is particularly beneficial for workloads involving streaming large datasets (e.g., video processing, natural language processing, or real-time inference). By reducing reliance on the CPU, GDS accelerates data movement and frees up CPU resources for other tasks—further enhancing overall system performance.
Read Throughput
Across our GDSIO sequential read testing, the Kingston DC3000ME demonstrated consistent, efficient throughput scaling across 16K, 128K, and 1MB block sizes—though performance trends varied slightly by transfer size. With 16K blocks, throughput rose steadily with increasing thread count, peaking at 3.70GiB/s by 32 threads before gradually tapering to 3.41GiB/s at 128 threads. For 128K transfers, the drive achieved its best result of 5.88GiB/s at 16 threads, maintaining that level through 32 threads before dropping to ~5.35GiB/s by 128 threads. At 1MB, throughput plateaued earlier—achieving 6.54GiB/s at 16 threads and declining modestly to 5.91GiB/s at 128 threads.
Read LatencyIn terms of latency, the DC3000ME showed predictable scaling (consistent with all tested drives): lower thread counts yielded lower response times across all block sizes, with latency increasing as threads scaled up. At 16K, latency started at 504µs and gradually increased to 582µs by 128 threads. For 128K, latency began at 260µs and increased to 3,228µs at the highest thread count. With 1MB blocks, latency showed a larger jump due to the heavier payload—starting at 2,609µs with one thread and increasing to 2,703µs at 128 threads.
Write ThroughputFor read operations, average latency with 16K blocks started at 2,247µs with a single thread and decreased to 504µs at 128 threads—demonstrating efficient scaling under concurrency. For 128K blocks, latency initially began at 4,035µs and gradually decreased to 2,601µs with 128 threads. With 1M blocks, the Kingston DC3000ME had the lowest latency overall—starting at 2,609µs with one thread and remaining in the 2,500–2,700µs range through 128 threads, demonstrating consistent responsiveness for large sequential reads.
Write LatencyAverage latency remained relatively stable across thread counts from 1 to 16, hovering around 12,234 to 14,247µs. At 32 threads, latency slightly increased to 15,559µs and climbed to 20,944µs at 64 threads. A notable spike occurred at 128 threads, where Kingston DC3000ME latency jumped to 28,725µs—more than doubling the prior level.
ConclusionThe Kingston DC3000ME is positioned as a practical solution for mainstream enterprise and data center deployments—where reliability, consistent performance, and a solid set of enterprise features are key requirements. This drive caters to system integrators, value-added resellers (VARs), and IT teams in SMB and SME environments that build and manage their own infrastructure. Its U.2 form factor and PCIe Gen5 support provide broad compatibility and future-ready bandwidth, making it a strong candidate for channel-driven deployments.
Kingston DC3000ME angleFrom a performance perspective, the DC3000ME delivers competitive throughput and efficiency across a range of workloads. Its strengths lie in solid sequential reads, good write consistency, and consistent latency scaling under mixed and random workloads. While it occasionally trails top Gen5 performers (e.g., Micron and SanDisk) in certain heavy CDN or checkpointing benchmarks, it remains competitive—especially in sustained mixed-load scenarios and moderate concurrency.
Overall, the DC3000ME is a strong fit for general-purpose enterprise workloads, meeting the needs of organizations looking to deploy high-performance storage without relying on highly customized OEM solutions. VARs and systems builders will find much to appreciate here, particularly when balancing cost, performance, and scalability in practical infrastructure deployments.
Beijing Qianxing Jietong Technology Co., Ltd.
Sandy Yang/Global Strategy Director
WhatsApp / WeChat: +86 13426366826
Email: yangyd@qianxingdata.com
Website: www.qianxingdata.com/www.storagesserver.com
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