With the focus on faster IOPS and lower power consuming
devices, there has been a lot of interest and buzz around Solid State Drives
(SSD). We explore some of the key talking points around SSD over here.
For a high level understanding perspective, most (not all) SSD’s
key characteristics are :
•
Semiconductor (NAND
flash, non-volatile)
•
No mechanical
read/write interface, no rotating parts eliminating seek time or rotational
delays
•
Electronically erasable medium
•
Random access storage
Through the various publications,
there is a general consensus that the flash memory-based SSDs provide lower
read/access latencies, higher read bandwidths, and minimal/negligible seek
overheads.
Some of the key gains which make SSD a
popular choice for column oriented database in NoSQL generation are :
“(1) SSDs scale up linearly with
concurrent execution of database queries and outperform disks by up to a factor of two,
(2) the low seek cost on SSDs makes column storage a better choice for laying
out data on a variety of flash devices,” (source : http://pages.cs.wisc.edu/~swift/papers/fdb-tr.pdf
)
From various experiments, it has become obvious that SSD can help reduce
computations and I/Os in MapReduce significantly. The observed advantage is
significant in sort map and sort reduce phases up to a tune of 30-40% on a
average. The advantage observed are primarily due to faster SSD throughput,
shorter IOWait while making more RAM available for processing. SSDs are best
suited for cache-unfriendly data with high access densities
(IOps/GB) requiring low response times.
Typical use case of SSD deployment include ATM, Online Banking, ATM, Currency
Trading, Point-of-Sale Transaction and data mining. Further from a green
footprint, SSD offer an additional benefit of lower energy consumption, cooling
and space requirements
However, flash memory architecture has also been criticized for “wear”
(loss of charge due to isolation defects) and low performance during “mix”
operation involving both read and write. There has also been a concern on high
cost per GB for SSD versus HDD. However, the cost gap is fast reducing with
market forces. With the concerns on enterprise adoption of SSD still a small
question mark, there has been a tendency to move to a hybrid architecture
involving both HDD and SSD with SSD taking the role of frontend or controller
to HDD. There have also been initiatives
for Tiered storage where data centers utilize different types of
storage throughout the storage infrastructure. For instance, SSD in Tier 0,
FC/SAS in Tier 1, SATA in Tier 2 layers. There is a key trend on moving to SSD for use cases where read
optimized database are deployed and primary use is to scan, select and fetch
data.
Over the years, SSD has made a key market presence and is expected to
grow up in maturity and price point to offer a valid option to enterprise for
much more storage options depending upon application architecture.
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