even rare accesses to HDD should be
performed in large granularities.
DRAM–SSD. SSDs are being increasingly used as the storage medium of
choice in the latency-critical performance tier due to their superior random
access capability compared to HDDs.
Thus, the five-minute rule can be used
to compute a break-even interval for the
case where DRAM is used to cache data
stored in SSDs. Table 3 shows the interval in 2007, when SSDs were in the initial stages of adoption, and today, based
on metrics listed in Table 1.
We see the interval has dropped
from 15 minutes to five minutes for
4KB pages. Thus, the five-minute rule
is valid for SSDs today. This is in stark
contrast with the DRAM–HDD case,
where the interval increased 2. 7× from
1. 5 hours to four hours. In both DRAM–
HDD and DRAM–SSD cases, the drop
in DRAM cost/MB dominated the eco-
nomic ratio. However, unlike the 2. 5×
improvement in random I/Os-per-
second (IOPS) with HDDs, SSDs have
managed to achieve an impressive 11×
improvement (67k/6.2k). Thus, the in-
crease in economic ratio was overshad-
owed by the decrease in technology ra-
tio with SSDs, resulting in the interval
SSD–HDD. As SSDs can also be used
as a cache for HDD, the same formula
can also be used to estimate the break-even interval for the SSD–HDD case.
From Table 3, we see the break-even
interval for this case has increased by
a factor of 10× from 2. 25 hours in 2007
to 1. 5 days in 2018. The SSD–HDD interval is nine times longer than the
DRAM–HDD interval of four hours.
Implications. There are two important consequences of these results.
First, in 2007, the turnover time in the
DRAM–HDD case was six times higher
than the DRAM–SSD case ( 1.5h/15m).
In 2018, it is nearly 50× higher (4h/5m).
Thus, in systems tuned using economic considerations, one should replace
HDD with SSD, as it would not only improve performance, but also reduce the
amount of DRAM required for caching data. Second, given the four-hour
DRAM–HDD and one day SSD–HDD intervals, it is important to keep all active
data in the DRAM or SSD-based performance tier and relegate the HDD-based capacity tier to storing only infrequently accessed data. The growing
gap between performance and capacity tiers also implies that SSD vendors
should optimize for $/IOPS, and HDD
vendors, in contrast, should optimize
for $/GB. Next, we highlight recent
changes in performance and capacity
tiers that indicate such targeted optimizations are already underway.
The Performance Tier
NAND flash. NAND flash-based solid-
state storage has been steadily inch-
ing its way closer to the CPU over the
past two decades. When NAND flash
was introduced in the early 2000s,
solid-state storage was dominated by
val was 400 seconds for 1KB pages. This
was rounded down to five minutes,
thus, lending the name for the rule. For
4KB pages, the break-even interval was
100 seconds. When the study was re-
peated in 1997, the break-even interval
had increased to nine minutes for 4KB
pages, and the five-minute rule was de-
termined to hold only for 8KB pages.
Between 1997 and 2007, DRAM and
HDD prices dropped further result-
ing in the economic ratio increasing
from 133 ($2k/$15) to 1700 ($80/$0.05).
However, the technology ratio did not
drop proportionately due to a lack of
improvement in HDD random access
latency. As a result, the break-even in-
terval for 4KB pages increased 10×,
from nine minutes to 1. 5 hours. The
five-minute rule was applicable only
for 64KB pages in 2007.
Continuing this trend, the break-even interval for DRAM–HDD case today is four hours for 4KB pages. The
five-minute rule is valid today for 512KB
pages. The break-even interval trend indicates it is more economical to store
most data in DRAM instead of the HDD,
and the page size trend indicates that
Table 1. The evolution of DRAM, HDD, and Flash SSD properties.
Metric DRAM HDD SATAFlash SSD
1987 1997 2007 2018 1987 1997 2007 2018 2007 2018
Unitprice($) 5k 15k 48 80 30k 2k 80 49 1k 415
Unitcapacity 1MB 1GB 1GB 16GB 180MB 9GB 250GB 2TB 32GB 800GB
$/MB 5k 14. 6 0.05 0.005 83. 33 0.22 0.0003 0.00002 0.03 0.0005
Random IOPS – – – – 5 64 83 200 6.2k 67k (r)/20k (w)
Sequential b/w (MB/s) – – – – 1 10 300 200 66 500 (r)/460 (w)
Figure 1. Storage tiering for enterprise databases.
Data Access Latency
ns ms secs mins µs