1 OVERVIEW In today's big data world, high performance databases are not only required but are a major part of any critical business function. With the advent of mobile devices, users are consuming data like never before requiring enterprises to serve large user populations and deliver highly responsive applications with no downtime. CTOs must make a prudent decision and thus seek out and investigate a database's performance characteristics to obtain a level of assurance that their database applications are both durable and scalable. They need the hard facts to back up such a critical business decision. Further more, this decision has to speak to the now and the future. The intent of this document is to provide database performance benchmarks for PostgreSQL across popular cloud platforms. This effort embodies some of the current architectures used by companies on those platforms. Results from such benchmarks can be as varied as the applications interfacing with them but the results included in this report can be used as a reference for running a high performance database on both Joyent and Amazon (AWS). TEST DESCRIPTION In our tests we analyzed the performance of PostgreSQL using several configurations of both Amazon EC2 and Joyent s public cloud. Our goal was to measure the performance of PostgreSQL utilizing an architecture and configuration that is widely used in production environments on comparable systems. Thus no tuning was done to either PostgreSQL itself or the servers themselves other than what is noted below. We certainly acknowledge that in expert hands both PostgreSQL and the servers they run on can be tuned to an astonishing degree. But these tunings may not be available or even advantageous on all systems and make valid side-by-side comparisons more and more difficult. For all the tests, PostgreSQL was set up in a Master/Slave configuration using asynchronous binary replication. On Amazon EC2 we tested 3 server configurations. The first EC2 configuration was a pair of M1 Large 7.5gb instances also optimized for EBS, and a 100gb EBS volume but was not set with provisioned IOPS. The second EC2 configuration was a pair of M1 Large 7.5gb instances also optimized for EBS, and a 100gb EBS volume provisioned with 3000 IOPS. The third EC2 configuration was a M3 Large 7.5gb instance using the 33gb SSD ephemeral (local) storage rather than an attached EBS volume. On Joyent s public cloud we tested a pair of Standard 7.5gb instances running SmartOS. On these instances we configured PostgreSQL to use the available 738gb local storage for data storage. The systems were tested using Yahoo Cloud Service Benchmark tool (YCSB) with 5 standard loads that demonstrate a variety of usage scenarios. YCSB is a purpose built tool that delivers a framework useful for evaluating different workloads on cloud platforms. YCSB has been used in more than 70 published benchmark comparisons and represents a standardized way to compare the performance between systems. For a more detailed description of the configuration of the machines used in these tests, please refer to the methodology section of this paper.
2 DATA LOADING To begin the work of testing various workloads, each system needed to be loaded with data. We loaded 6 million records that contained 10 fields of 100 bytes of data each, creating 1k of data per record. The total table size was 6gb. optimized for EBS performed an average of 2,523.4 ops/s, with provisioned IOPS performed an average of 4,146.8 ops/s, performed 4,820.8 ops/s. performed 15,225.5 ops/s. Comparatively, was 603% faster than optimized, 367% faster than with provisioned IOPS and 316% faster than. The total load time for optimized was 2,300 seconds, for with provisioned IOPS was 1,447 seconds, for AWS M3 was 1,245 seconds and 394 seconds for Joyent SmartOS , , , , , ,820.8 EBS
3 50% READ, 50% UPDATE The 50% read, 50% update workload represents a workload similar to a session store that is recording recent actions. 50% of the operations are read operations while 50% are updates of an existing record. optimized for EBS performed an average of ops/s, with provisioned IOPS performed an average of 1,642.3 ops/s, performed 3,919.0 ops/s. performed 5,969.5 ops/s. Comparatively, was 1,263% faster than optimized, 363% faster than with provisioned IOPS and 152% faster than. The total load time for optimized was 1,058 seconds, for with provisioned IOPS was 304 seconds, for AWS M3 was 128 seconds and 84 seconds for Joyent SmartOS. 7, , , , , , ,642.3 EBS
4 95% READ, 5% UPDATE The 95% read, 5% update workload represents a workload similar to a photo tagging website where a photo is viewed frequently and tags are updated to the photo s data. 95% of the operations are read operations of a single record and 5% are updates. optimized for EBS performed an average of ops/s, with provisioned IOPS performed an average of 2,655.7 ops/s, performed 4,634.3 ops/s. performed 11,033.6 ops/s. Comparatively, was 1,404% faster than optimized, 415% faster than with provisioned IOPS and 238% faster than. The total load time for optimized was 636 seconds, for with provisioned IOPS was 188 seconds, for AWS M3 was 108 seconds and 45 seconds for Joyent SmartOS. 1 10, , , , ,634.3 EBS
5 100% READ The 100% read workload represents a static dataset such as a user profile cache where profiles are constructed infrequently but read often. No operations write to the database under this test. optimized for EBS performed an average of ops/s, with provisioned IOPS performed an average of 3,216.3 ops/s, performed 4,850.0 ops/s. performed 9,042.1 ops/s. Comparatively, was 1,186% faster than optimized, 281% faster than with provisioned IOPS and 186% faster than. The total load time for optimized was 656 seconds, for with provisioned IOPS was 155 seconds, for AWS M3 was 103 seconds and 55 seconds for Joyent SmartOS. 10, , , , ,216.3 EBS EBS
6 95% READ, 5% INSERT The 95% read, 5% insert workload represents a usage similar to status updates where the latest records are also the records most likely to be read. 95% of the operations are read operations and 5% are inserts of new records into the database. optimized for EBS performed an average of 2,486.4 ops/s, with provisioned IOPS performed an average of 3,742.1 ops/s, performed 4,393.1 ops/s. performed 7,382.3 ops/s. Comparatively, was 297% faster than optimized, 197% faster than with provisioned IOPS and 168% faster than. The total load time for optimized was 201 seconds, for with provisioned IOPS was 134 seconds, for AWS M3 was 114 seconds and 45 seconds for Joyent SmartOS. 8, , , , , , , , ,486.4 EBS
7 50% READ, 50% READ MODIFY WRITE The 50% read, 50% read modify write represents a workload that simulates users reading and modifying the record read. 50% of the operations are read operations of a single record, and 50% are a read of a single record, modification of the record retrieved and a subsequent save of the modification back to the database. optimized for EBS performed an average of ops/s, with provisioned IOPS performed an average of 1,581.2 ops/s, performed 3,198.6 ops/s. performed 6,780.9 ops/s. Comparatively, was 1544% faster than optimized, 429% faster than with provisioned IOPS and 212% faster than. The total load time for optimized was 1,138 seconds, for with provisioned IOPS was 316 seconds, for AWS M3 was 156 seconds and 61 seconds for Joyent SmartOS. 8, , , , , , , ,581.2 EBS
9 Methodology In order to test the performance of the PostgreSQL across various cloud platform configurations, we set up several pairs of PostgreSQL in a master/slave configuration with each server configured identically. The slave server was set to use asynchronous binary replication and was set to be in hot standby mode. Each PostgreSQL server was configured to accept up to 1,000 connections and its shared buffers size was increased to 2 gigabytes. At Joyent, we created a master/slave PostgreSQL pair using Standard 7.5gb instances for both the master and slave servers. The 7.5gb machine was equipped with 2 virtual CPUs, a 738gb disk and up to 10Gbit/s network access. Definitions YCSB Yahoo Cloud Service Benchmark tool. The tool is available from github at github.com/brianfrankcooper/ycsb Operations per second as reported from both the YCSB tool. While not officially part of the cluster, a Standard 3.75gb instance was created to be used as a YCSB client machine using the same operating system used with that server pair. In addition the YCSB client was within the same internal network to allow communication using the internal network IP rather than the public IP address. At Amazon, we created a master/slave postgres pair in three different EC2 configurations; M1 Large EBS, M1 Large EBS with provisioned IOPS, and M3 SSD ephemeral disk (without EBS). In each case, CentOS 6.4 was used from the disk image provided from CentOS.org (community AMI ami-b3bf2f83). Also each instance was set to single tenant to prevent noisy neighbors from disturbing the test. The first AWS configuration used m1.large 7.5gb single tenant instances. large instances have 2 virtual CPUs, 840gb ephemeral storage (which was not used) and 500 Mbps network access. Each server was configured to run as EBS and was configured with a 100gb EBS volume. The EBS volume used the ext4 file system. To improve the performance of the ext4 file system, we set the following mount options; noatime,nodiratime,data=writeback,barrier=0,nobh,errors=remount-ro. The second AWS configuration used m1.large 7.5gb single tenant instances. large instances have 2 virtual CPUs, 840gb ephemeral storage (which was not used) and 500 Mbps network access. Each server was configured to run as EBS and was configured with a 100gb EBS volume. The EBS volume was provisioned with 3,000 IOPS, the maximum IOPS available. The EBS volume used the ext4 file system. To improve the performance of the ext4 file system, we set the following mount options; noatime,nodiratime,data=writeback,barrier=0,nobh,errors=remount-ro. The third AWS configuration used m3.large 7.5gb single tenant instances. AWS M3 large instances have 2 virtual CPUs, 32gb ephemeral storage and moderate network performance. The 32gb storage is SSD based disk and was configured for use at the time of launch. A small 8gb EBS volume was also added to these instances because the CentOS AMI used required EBS storage to run. These EBS volumes were otherwise not used. As with the M1 instances, the ephemeral storage used an ext4 file system, which was set with the same mount options as the AWS M1 instances. While not officially part of the cluster, a Standard 3.75gb m3.medium instance was created to be used as a YCSB client machine using the same operating system used with that server pair. In addition the YCSB client was within the same internal network to allow communication using the internal network IP rather than the public IP address.
10 Yahoo Cloud Service Benchmark Tool The benchmarking tests were performed using the Yahoo Cloud Service Benchmark (YCSB) tool, which provided a consistent framework for loading, and running various test scenarios. YCSB was developed at Yahoo Labs to assist in evaluating various key-value and cloud databases. Since the publication of Benchmarking Cloud Serving Systems with YCSB ( in 2010 and release of the YCSB source code, over 70 publications have used the tool for various benchmark comparisons. While it is possible to run the YCSB tool locally on the same machine as the database server, we chose to run it on a separate instance in order to prevent any possible interference with the CPU or memory of the machines under test. YCSB allows the user to set the number of threads and a target number of operations per second. We found that setting the thread count to 50 gave the highest operations per second. We initially loaded each cluster with 6 million records. Each record contained 10 fields of 100 bytes each and the entire data size was approximately 6gb. Each workload test was run for 500,000 operations.
How AWS Pricing Works May 2015 (Please consult http://aws.amazon.com/whitepapers/ for the latest version of this paper) Page 1 of 15 Table of Contents Table of Contents... 2 Abstract... 3 Introduction...
BENCHMARKING AVAILABILITY AND FAILOVER PERFORMANCE OF LARGE-SCALE DATA STORAGE APPLICATIONS Wei Sun and Alexander Pokluda December 2, 2013 Outline Goal and Motivation Overview of Cassandra and Voldemort
How AWS Pricing Works (Please consult http://aws.amazon.com/whitepapers/ for the latest version of this paper) Page 1 of 15 Table of Contents Table of Contents... 2 Abstract... 3 Introduction... 3 Fundamental
Amazon EC2 Product Details Page 1 of 5 Amazon EC2 Functionality Amazon EC2 presents a true virtual computing environment, allowing you to use web service interfaces to launch instances with a variety of
Amazon Cloud Storage Options Table of Contents 1. Overview of AWS Storage Options 02 2. Why you should use the AWS Storage 02 3. How to get Data into the AWS.03 4. Types of AWS Storage Options.03 5. Object
Creating Value Delivering Solutions Technology and Cost Considerations for Cloud Deployment: Amazon Elastic Compute Cloud (EC2) Case Study Chris Zajac, NJDOT Bud Luo, Ph.D., Michael Baker Jr., Inc. Overview
Benchmarking Couchbase Server for Interactive Applications By Alexey Diomin and Kirill Grigorchuk Contents 1. Introduction... 3 2. A brief overview of Cassandra, MongoDB, and Couchbase... 3 3. Key criteria
Parallels Cloud Storage White Paper Performance Benchmark Results www.parallels.com Table of Contents Executive Summary... 3 Architecture Overview... 3 Key Features... 4 No Special Hardware Requirements...
P3 InfoTech Solutions Pvt. Ltd http://www.p3infotech.in July 2013 Created by P3 InfoTech Solutions Pvt. Ltd., http://p3infotech.in 1 Web Application Deployment in the Cloud Using Amazon Web Services From
Deep Dive: Maximizing EC2 & EBS Performance Tom Maddox, Solutions Architect 2015, Amazon Web Services, Inc. or its affiliates. All rights reserved What we ll cover Amazon EBS overview Volumes Snapshots
Comparing Couchbase Server 3.0.2 with MongoDB 3.0: Benchmark Results and Analysis Composed by Avalon Consulting, LLC Introduction The data needs of today s Enterprise require a special set of tools. At
WHITEPAPER Accelerating Enterprise Applications and Reducing TCO with SanDisk ZetaScale Software SanDisk ZetaScale software unlocks the full benefits of flash for In-Memory Compute and NoSQL applications
Benchmark Results of Fengqi.Asia Fengqi.Asia SmartOS SmartMachine vs. Popular Cloud Platforms(Part A) Fengqi.Asia VirtualMachine vs. Popular Cloud Platforms(Part B) Prepared by Fengqi.Asia Copyright owned
1. Computation Amazon Web Services Amazon Elastic Compute Cloud (Amazon EC2) provides basic computation service in AWS. It presents a virtual computing environment and enables resizable compute capacity.
Fault-Tolerant Computer System Design ECE 695/CS 590 Putting it All Together Saurabh Bagchi ECE/CS Purdue University ECE 695/CS 590 1 Outline Looking at some practical systems that integrate multiple techniques
Cloud Computing and E-Commerce Cloud Computing turns Computing Power into a Virtual Good for E-Commerrce is Implementation Partner of 4FriendsOnly.com Internet Technologies AG VirtualGoods, Koblenz, September
Getting Started with SandStorm NoSQL Benchmark SandStorm is an enterprise performance testing tool for web, mobile, cloud and big data applications. It provides a framework for benchmarking NoSQL, Hadoop,
19.10.11 Amazon Elastic Beanstalk A Short History of AWS Amazon started as an ECommerce startup Original architecture was restructured to be more scalable and easier to maintain Competitive pressure for
White Paper October 2014 Scaling MySQL Deployments Using HGST FlashMAX PCIe SSDs An HGST and Percona Collaborative Whitepaper Table of Contents Introduction The Challenge Read Workload Scaling...1 Write
Determining the IOPS Needs for Oracle Database on AWS Abdul Sathar Sait Jinyoung Jung Amazon Web Services December 2014 Last update: April 2016 Contents Abstract 2 Introduction 2 Storage Options for Oracle
Performance Analysis: Benchmarking Public Clouds Performance comparison of web server and database VMs on Internap AgileCLOUD and Amazon Web Services By Cloud Spectator March 215 PERFORMANCE REPORT WEB
Performance Benchmark for Cloud Block Storage J.R. Arredondo vjune2013 Contents Fundamentals of performance in block storage Description of the Performance Benchmark test Cost of performance comparison
Technical White Paper Report Technical Report Benchmarking Cassandra on Violin Accelerating Cassandra Performance and Reducing Read Latency With Violin Memory Flash-based Storage Arrays Version 1.0 Abstract
BENCHMARKING CLOUD DATABASES CASE STUDY on HBASE, HADOOP and CASSANDRA USING YCSB Planet Size Data!? Gartner s 10 key IT trends for 2012 unstructured data will grow some 80% over the course of the next
An Esri White Paper January 2011 Estimating the Cost of a GIS in the Amazon Cloud Esri, 380 New York St., Redlands, CA 92373-8100 USA TEL 909-793-2853 FAX 909-793-5953 E-MAIL email@example.com WEB esri.com
Technical White Paper Report Technical Report Benchmarking Hadoop & HBase on Violin Harnessing Big Data Analytics at the Speed of Memory Version 1.0 Abstract The purpose of benchmarking is to show advantages
Introduction to AWS Economics Reducing Costs and Complexity May 2015 2015, Amazon Web Services, Inc. or its affiliates. All rights reserved. Notices This document is provided for informational purposes
Best Practices for Using MySQL in the Cloud Luis Soares, Sr. Software Engineer, MySQL Replication, Oracle Lars Thalmann, Director Replication, Backup, Utilities and Connectors THE FOLLOWING IS INTENDED
Amazon Hosted ESRI ArcGIS Servers Project Final Report Description of Application National Center for Education Statistics Operating Organization The US Department of Education s (ED) The National Center
Intro to AWS: Storage Services Matt McClean, AWS Solutions Architect 2015, Amazon Web Services, Inc. or its affiliates. All rights reserved AWS storage options Scalable object storage Inexpensive archive
CLOUD COMPUTING PRACTICE 82 Chapter 9 PUBLIC CLOUD LABORATORY Hand on laboratory based on AWS Sucha Smanchat, PhD Faculty of Information Technology King Mongkut s University of Technology North Bangkok
Implementing Cirrus Data Solutions DCS SAN Caching Appliance With the Seagate Nytro Technology Paper Authored by Rick Stehno, Principal Database Engineer, Seagate Introduction Supporting high transaction
GeoCloud Project Report GEOSS Clearinghouse Qunying Huang, Doug Nebert, Chaowei Yang, Kai Liu 2011.12.06 Description of Application GEOSS clearinghouse is a FGDC, GEO, and NASA project that connects directly
THE DEFINITIVE GUIDE FOR AWS CLOUD EC2 FAMILIES Introduction Amazon Web Services (AWS), which was officially launched in 2006, offers you varying cloud services that are not only cost effective, but also
Amazon Web Services Primer William Strickland COP 6938 Fall 2012 University of Central Florida AWS Overview Amazon Web Services (AWS) is a collection of varying remote computing provided by Amazon.com.
Copyright www.agileload.com 1 INTRODUCTION Performance testing is a complex activity where dozens of factors contribute to its success and effective usage of all those factors is necessary to get the accurate
Using Synology SSD Technology to Enhance System Performance Synology Inc. Synology_SSD_Cache_WP_ 20140512 Table of Contents Chapter 1: Enterprise Challenges and SSD Cache as Solution Enterprise Challenges...
UBUNTU DISK IO BENCHMARK TEST RESULTS FOR JOYENT Revision 2 January 5 th, 2010 The IMS Company Scope: This report summarizes the Disk Input Output (IO) benchmark testing performed in December of 2010 for
Développement logiciel pour le Cloud (TLC) 7. Infrastructure-as-a-Service Guillaume Pierre Université de Rennes 1 Fall 2012 http://www.globule.org/~gpierre/ Développement logiciel pour le Cloud (TLC) 1
QLIKVIEW INTEGRATION TION WITH AMAZON REDSHIFT John Park Partner Engineering June 2014 Page 1 Contents Introduction... 3 About Amazon Web Services (AWS)... 3 About Amazon Redshift... 3 QlikView on AWS...
Zadara Storage Cloud A whitepaper @ZadaraStorage Zadara delivers two solutions to its customers: On- premises storage arrays Storage as a service from 31 locations globally (and counting) Some Zadara customers
MaxDeploy Ready Hyper- Converged Virtualization Solution With SanDisk Fusion iomemory products MaxDeploy Ready products are configured and tested for support with Maxta software- defined storage and with
HyperQ Hybrid Flash Storage Made Easy White Paper Parsec Labs, LLC. 7101 Northland Circle North, Suite 105 Brooklyn Park, MN 55428 USA 1-763-219-8811 www.parseclabs.com firstname.lastname@example.org email@example.com
HyperQ Storage Tiering White Paper An Easy Way to Deal with Data Growth Parsec Labs, LLC. 7101 Northland Circle North, Suite 105 Brooklyn Park, MN 55428 USA 1-763-219-8811 www.parseclabs.com firstname.lastname@example.org
Using SUSE Studio to Build and Deploy Applications on Amazon EC2 Guide Solution Guide Cloud Computing Cloud Computing Solution Guide Using SUSE Studio to Build and Deploy Applications on Amazon EC2 Quickly
Building a Private Cloud with Eucalyptus 5th IEEE International Conference on e-science Oxford December 9th 2009 Christian Baun, Marcel Kunze KIT The cooperation of Forschungszentrum Karlsruhe GmbH und
Scaling Database Performance in Azure Results of Microsoft-funded Testing Q1 2015 2015 2014 ScaleArc. All Rights Reserved. 1 Test Goals and Background Info Test Goals and Setup Test goals Microsoft commissioned
Cloud Based Application Architectures using Smart Computing How to Use this Guide Joyent Smart Technology represents a sophisticated evolution in cloud computing infrastructure. Most cloud computing products
Amazon Elastic Compute Cloud Getting Started Guide My experience Prepare Cell Phone Credit Card Register & Activate Pricing(Singapore) Region Amazon EC2 running Linux(SUSE Linux Windows Windows with SQL
DISTRIBUTED SYSTEMS [COMP9243] Lecture 9a: Cloud Computing Slide 1 Slide 3 A style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet.
MySQL and Virtualization Guide Abstract This is the MySQL and Virtualization extract from the MySQL Reference Manual. For legal information, see the Legal Notices. For help with using MySQL, please visit
Cloud Computing Performance Benchmark Testing Report Comparing vs. Amazon EC2 April 2014 Contents The Cloud Computing Performance Benchmark report is divided into several sections: Topics.Page Introduction...
Amazon Hosted ESRI GeoPortal Server GeoCloud Project Report Description of Application Operating Organization The USDA participated in the FY 2011 Federal Geographic Data Committee (FGDC) GeoCloud Sandbox
Cloud Computing Performance Benchmarking Report Comparing and Amazon EC2 using standard open source tools UnixBench, DBENCH and Iperf October 2014 TABLE OF CONTENTS The Cloud Computing Performance Benchmark
Eloquence Training What s new in Eloquence B.08.00 2010 Marxmeier Software AG Rev:100727 Overview Released December 2008 Supported until November 2013 Supports 32-bit and 64-bit platforms HP-UX Itanium
USER CONFERENCE 2011 SAN FRANCISCO APRIL 26 29 Running MarkLogic in the Cloud DEVELOPER LOUNGE LAB Table of Contents UNIT 1: Lab description... 3 Pre-requisites:... 3 UNIT 2: Launching an instance on EC2...
Performance Benchmark for Cloud Databases J.R. Arredondo vjune2013 (updated pricing on 7/15/2013) Contents Summary of the performance benchmark tests Description of the tests Charts and Data! Results of
The Secret World of Cloud IaaS Pricing in 2014: How to Compare Apples and Oranges Among Cloud Providers TABLE OF CONTENTS: EXECUTIVE SUMMARY... 3 PART 1: THE CURRENT STATE OF CLOUD COMPUTING IAAS: PRICING
Copyright 2014 Splunk Inc. Deploying Splunk on Amazon Web Services Simeon Yep Senior Manager, Business Development Technical Services Roy Arsan Senior SoHware Engineer Disclaimer During the course of this
Use of Cloud Computing for scalable geospatial data processing and access Andrew Turner CTO, FortiusOne email@example.com Partner: U.S. Federal Geographic Data Committee What is GeoCommons? A Brief
CA ARCserve Replication and CA ARCserve High Availability r16 CA ARCserve Replication and CA ARCserve High Availability Deployment Options for Microsoft Hyper-V Server TYPICALLY, IT COST REDUCTION INITIATIVES
OpenStack Orgad Kimchi Principal Software Engineer Oracle ISV Engineering 1 Copyright 2013, Oracle and/or its affiliates. All rights reserved. Safe Harbor Statement The following is intended to outline
MySQL: Cloud vs Bare Metal, Performance and Reliability Los Angeles MySQL Meetup Vladimir Fedorkov, March 31, 2014 Let s meet each other Performance geek All kinds MySQL and some Sphinx Working for Blackbird
Cloud Computing and Amazon Web Services Gary A. McGilvary edinburgh data.intensive research 1 OUTLINE 1. An Overview of Cloud Computing 2. Amazon Web Services 3. Amazon EC2 Tutorial 4. Conclusions 2 CLOUD
Common Server Setups For Your Web Application - Part II Introduction When deciding which server architecture to use for your environment, there are many factors to consider, such as performance, scalability,
FortiGate Amazon Machine Image (AMI) Selection Guide for Amazon EC2 New Place, Same Feel Secure Your AWS Cloud with Fortinet Fortinet s Amazon Machine Image (AMI) and subscription based portfolio offer
Contract 11 Test Delivery System American Institutes for Research Revision History Revision Description Author/Modifier Date Initial Release David Lopez de Quintana October 14, 2013 Updated to latest Amazon
NV-DIMM: Fastest Tier in Your Storage Strategy Introducing ArxCis-NV, a Non-Volatile DIMM Author: Adrian Proctor, Viking Technology [email: firstname.lastname@example.org] This paper reviews how Non-Volatile
Price Comparison / AWS EC2 M3 Instances Produced by, Inc. Additional Information and access to a 14- day trial are avaialble at: http://www.profitbricks.com Getting Started: Comparing Infrastructure- as-
SDFS Overview By Sam Silverberg Why did I do this? I had an Idea that I needed to see if it worked. Design Goals Create a dedup file system capable of effective inline deduplication for Virtual Machines
on AWS Services Overview Bernie Nallamotu Principle Solutions Architect \ So what is it? When your data sets become so large that you have to start innovating around how to collect, store, organize, analyze
Contract 11 Test Delivery System American Institutes for Research Revision History Revision Description Author/Modifier Date Initial Release David Lopez de Quintana October 14, 2013 Contents 4 Overview...
Technology Insight Paper Coho Data s DataStream Clustered NAS System Bridging a Gap Between Webscale and Enterprise IT Storage By John Webster November, 2014 Enabling you to make the best technology decisions
PipeCloud : Using Causality to Overcome Speed-of-Light Delays in Cloud-Based Disaster Recovery Razvan Ghitulete Vrije Universiteit Introduction /introduction Ubiquity: the final frontier Internet needs
Using Synology SSD Technology to Enhance System Performance Synology Inc. Synology_WP_ 20121112 Table of Contents Chapter 1: Enterprise Challenges and SSD Cache as Solution Enterprise Challenges... 3 SSD
Esri Middle East and Africa User Conference December 10 12 Abu Dhabi, UAE Understanding ArcGIS in Virtualization and Cloud Environments Marwa Mabrouk Powerful GIS capabilities Delivered as Web services