Skip to main content

The buzz and fuss on SSD

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 : )

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.


Popular posts from this blog

Beyond NSA, the intelligence community has a big technology footprint

While all through the past few days the focus has been on NSA activities, the discussion has often veered around the technologies and products used by NSA. At the same time, a side discussion topic has been the larger technical ecosystem of intelligence units. CIA has been one of the more prolific users of Information Technology by its own admission. To that extent, CIA spinned off a venture capital firm In-Q-Tel in 1999 to invest in focused sector companies. Per Helen Coster of Fortune Magazine, In-Q-Tel (IQT) has been named “after the gadget-toting James Bond character Q”.
In-Q-Tel states on its website that “We design our strategic investments to accelerate product development and delivery for this ready-soon innovation, and specifically to help companies add capabilities needed by our customers in the Intelligence Community”. To that effect, it has made over 200 investments in early stage companies for propping up products. Being a not-for-profit group, unlike Private Venture capi…

Data deduplication tactics with HDFS and MapReduce

As the amount of data continues to grow exponentially, there has been increased focus on stored data reduction methods. Data compression, single instance store and data deduplication are among the common techniques employed for stored data reduction.
Deduplication often refers to elimination of redundant subfiles (also known as chunks, blocks, or extents). Unlike compression, data is not changed and eliminates storage capacity for identical data. Data deduplication offers significant advantage in terms of reduction in storage, network bandwidth and promises increased scalability.
From a simplistic use case perspective, we can see application in removing duplicates in Call Detail Record (CDR) for a Telecom carrier. Similarly, we may apply the technique to optimize on network traffic carrying the same data packets.
Some of the common methods for data deduplication in storage architecture include hashing, binary comparison and delta differencing. In this post, we focus on how MapReduce and…

Top Big Data Influencers of 2015

2015 was an exciting year for big data and hadoop ecosystem. We saw hadoop becoming an essential part of data management strategy of almost all major enterprise organizations. There is cut throat competition among IT vendors now to help realize the vision of data hub, data lake and data warehouse with Hadoop and Spark.
As part of its annual assessment of big data and hadoop ecosystem, HadoopSphere publishes a list of top big data influencers each year. The list is derived based on a scientific methodology which involves assessing various parameters in each category of influencers. HadoopSphere Top Big Data Influencers list reflects the people, products, organizations and portals that exercised the most influence on big data and ecosystem in a particular year. The influencers have been listed in the following categories:

AnalystsSocial MediaOnline MediaProductsTechiesCoachThought LeadersClick here to read the methodology used.

Analysts:Doug HenschenIt might have been hard to miss Doug…