Rick Stehno Principle Product Marketing Engineer / DBA
What is an Oracle NoSQL Database?
According to Oracle, “The Oracle NoSQL Database is a distributed key-value database. It is designed to provide highly reliable, scalable, and available data storage across a configurable set of systems that function as storage nodes.” 1
Oracle is not new at creating databases. The company’s foundation was laid with the development of its relational database back in the late 1970s and 1980s. Since the mid-2000s, Oracle started acquiring software companies and revamping the software in order to deliver a NoSQL database that would meet the enterprise standards that Oracle applied to its other database and application offerings. The Berkeley DB is used as the core of the NoSQL database. The Berkeley DB library provides a building block (made up of application program interfaces or APIs) of database features and functionality that C, C++, Perl, Python, Ruby XML, and Java programmers can embed into their applications. Many open source projects such as Linux, BSD, Apache web server, OpenLDAP, and many others embed Berkeley DB technology.
Most big data databases don’t offer ACID (atomic, consistent, isolated, durable) compliance, but offer BASE (basically available, soft state, eventually consistent) compliance. The Oracle NoSQL database provides ACID transactions fault recovery, high concurrency, and replication for highly available (HA) applications.
In deploying an Oracle NoSQL Database, the application makes simple database function calls to interact with the storage layer instead of writing complicated queries in the business layer. The following figu e provides a high-level illustration of an Oracle NoSQL implementation:
What is a Nytro acceleration card?
The Nytro application acceleration cards are designed to offer high performance with exceptionally low latency with a low CPU burden. The Nytro cards help accelerate applications such as web serving, data warehousing, data mining, online transaction processing and high-performance computing. Their PCIe® host interface, industry standard drivers, and small form factor make them more flexible and easier to integrate into today’s low profile, high performance system chassis.
The Nytro cards are built on the latest enterprise level solid state technologies and include sophisticated advanced features to help deliver consistently high levels of performance, endurance, and reliability under some of the most demanding conditions. In addition, the SandForce DuraWrite™ technology helps optimize the number of program cycles to the flash storage effectively extending the rated write endurance of the flash storage by up to 8x or more when compared to some other controllers.
Other sophisticated algorithms and dedicated onboard hardware resources handle complex flash management tasks like garbage collection and wear leveling. These advanced features make the Nytro cards an excellent choice for accelerating your business applications.1
The following benchmark tests were run on a single shard consisting of three server storage nodes, with one of these storage server nodes acting as both a storage node and an administrative node. Server specifics are defined below.
The benchmark used was the Yahoo Cloud Systems Benchmark (YCSB)2. The YCSB framework is intended to facilitate performance comparisons of the new generation of cloud data serving systems, employing a defined core set of benchmarks and report results for widely used database systems. In addition to making it easier to benchmark new systems, the YCSB framework is extensible in that it supports easier definition of new workloads.
Each server storage node consisted of the following hardware/soft-ware
Supermicro: Dual 6 Core Xeon 5650 2.67Ghz
Oracle Unbreakable Enterprise Kernel (UEK) 2.6.39-300
Oracle NoSQL Database:
NoSQL DB 11gR188.8.131.52 2012-11-26
For the HDD baseline test, single 300G capacity
Nytro Acceleration Card:
Storage Node 2 was also used as the Admin Node
Note: Total throughput was limited for the Nytro ard because of swapping issues on the storage/admin node. The other two (2) storage nodes did not have swap issues and were only 25% busy during these benchmarks.
YCSB Configuration Parameters:
Topology transformation from current deployed topology to MyStoreLayout:
Create 1 shard
Create 3 RNs
Create 10 partitions
RECORDCOUNT_PER_SHARD=100000000 # 100,000,000 (100M)
YCSB_LOB_SIZE=1000000 # 1,000,000 (1M)
|YCSB Stats||HDD – 300G||Nytro Card||Performance Gains w/Nytro|
|Throughput Mixed Operations/sec||2069||96589||4668%|
|Read (ms) Average
|Update (ms) Average
Throughput: 21182 insert ops/sec 2069 mixed ops/sec
[INSERT] insert count:99999960 latency (av/95%/99%):5.65/8/67 ms
[READ] read count:9499445 latency (av/95%/99%):50.51/217/390 ms
[UPDATE] update count:500545 latency (av/95%/99%):51.31/218/391 ms
Throughput: 27803 insert ops/sec 96589 mixed ops/sec
[INSERT] insert count:99999900 latency (av/95%/99%):5.38/8/11 ms
[READ] read count:9500689 latency (av/95%/99%):1.00/2/4 ms
[UPDATE] update count:499271 latency (av/95%/99%):4.15/6/48 ms
IOSTAT Report During Mixed Operations
What Do These Statistics Point Out?
The hardware and software were originally set up similar to a typical enterprise installation. To establish the baseline, a single 300GB HDD was used. The goal of the benchmark was to capture any performance improvement that resulted when a customer with an existing running system implemented the Nytro acceleration card..
Overall, the benchmark results show an average of 10x performance gains throughout, with some statistics showing over a 50x gain in performance.
Overall, the performance gains were impressive when implementing the Nytro acceleration card, even with no other modifications. With very little effort from the Oracle NoSQL Database administrator or developer, it is possible to achieve large performance gains by implementing a Nytro acceleration card into an existing Oracle NoSQL Database infrastructure.
The combination of the Nytro acceleration card and Oracle NoSQL Database can provide enterprises with a great solution for increasing the performance of a big data deployment. With such a solution, one can achieve optimized performance without the large costs and manual effort typically associated when implementing such a configuration.
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