Click here to close now.

Welcome!

Virtualization Authors: Carmen Gonzalez, Pat Romanski, Elizabeth White, Leo Reiter, Mike Kavis

Related Topics: Cloud Expo

Cloud Expo: Blog Post

The Economics of Big Data: Why Faster Software is Cheaper

Faster means better and cheaper - lower latency and lower cost!

In big data computing, and more generally in all commercial highly parallel software systems, speed matters more than just about anything else. The reason is straightforward, and has been known for decades.

Put very simply, when it comes to massively parallel software of the kind need to handle big data, fast is both better AND cheaper. Faster means lower latency AND lower cost.

At first this may seem counterintuitive. A high-end sports car will be much faster than a standard family sedan, but the family sedan may be much cheaper. Cheaper to buy, and cheaper to run. But massively parallel software running on commodity hardware is a quite different type of product from a car. In general, the faster it goes, the cheaper it is to run.

Time Is Money
As has been noted many times in the history of computing, if you are a factor of 50x slower, then you will need 50x more nodes to run at the same speed (even assuming perfect parallelization), or your computation will need 50x more time. In either case, it will also be much more likely that you will experience at least one of your nodes crashing during a computation. This is not to argue that automatic fault tolerance and recovery should be ignored in the pursuit of speed, but rather that these two factors need to be carefully balanced. Good design in massively parallel systems is about achieving maximum speed along with the ability to recover from a given expected level of hardware failure, via checkpointing.

The key phrase here is "a given expected level of hardware failure". In certain types of peer-to-peer services which take advantage of idle PC capacity, it is necessary to assume that all machines are extremely unreliable and may go offline at any time. However, in a commercial big data cluster it may be reasonably asssumed that almost all machines will be available almost all of the time. This means that a much more optimistic point in the design space can be chosen, one which is designed much more for speed than for pathological failure scenarios.

The MapReduce model is an example of a model where speed has been sacrificed in a major way in order to achieve scalability on very unreliable hardware. As we have noted, while this is acceptable in certain types of free peer-to-peer services, it is much less acceptable in commercial big data systems deployed at scale.

Google, the inventors of the model, were the first to recognize the throughput and latency problems with the MapReduce model. To get the realtime performance they required, they recently replaced MapReduce in their Google Instant search engine.

The MapReduce model of Apache Hadoop is slow. In fact, it's very slow compared to, for example, the kinds of MPI or BSP clusters that have been routinely used in supercomputing for more than 15 years. On exactly the same hardware, MapReduce can be several orders of magnitude slower than MPI or BSP. By using MPI rather than MapReduce, HadoopBI gives customers the best possible big data solution, not only in terms of performance - massive throughput and extremely low latency - but also in terms of economics. HadoopBI is not just the fastest Big Data BI solution, it is also the cheapest at scale.

It's Free, But Is It Fast Enough?
Another frequently misunderstood element of big data economics concerns so-called "free" software. It has been argued by some that, since big data software needs to be run on many nodes, it is really important to have software that is free. Again this is an extreme oversimplification that ignores the dominant cost issues in big data economics. At large scale, software costs will in general be much smaller than hardware or cloud costs. And commercial software vendors should ensure that they are, if they want to stay in business.

Consider the following small-scale example. A company needs to process big data continuously in order to maximize competitive advantage. For simplicity, we will assume that the cost of running a single server (in-house or cloud) for one hour is $1, and that the company has a choice between two big data software systems - system A costs $1,000 per server and system B is free, but system A is 8x faster. Choosing system A, the company requires 5 servers, working continuously, to achieve the throughput required. However, if the company chooses system B, it will require 40 servers running continuously.

Simple arithmetic shows that within just six days, the initial cost of system A has been recovered, and from then on system A gives the company massive cost savings. Even if system A is only 2x or 3x faster and more efficient than system B, the initial cost will still be recovered in a matter of a few weeks.

The economic advantages of speed at scale are magnified even more in large-scale big data systems where, with volume licensing discounts, the payback time for super-fast software is even shorter.

The lesson of the above example is simple and very important. In parallel systems, speed at scale is king, as speed equates to efficiency, and efficiency equates to massive cost savings at scale. So, to be relevant for large scale production deployments, free parallel software has to be at least as fast and efficient as the best commercial software, otherwise the economics will be solidly against it. Some examples of free software, such as the Linux operating system, have achieved this goal. It remains to be seen whether this will also be the case with highly parallel big data software. In the meantime, it's important to remember that "free software is cheap, but fast software can be even cheaper".

More Stories By Bill McColl

Bill McColl left Oxford University to found Cloudscale. At Oxford he was Professor of Computer Science, Head of the Parallel Computing Research Center, and Chairman of the Computer Science Faculty. Along with Les Valiant of Harvard, he developed the BSP approach to parallel programming. He has led research, product, and business teams, in a number of areas: massively parallel algorithms and architectures, parallel programming languages and tools, datacenter virtualization, realtime stream processing, big data analytics, and cloud computing. He lives in Palo Alto, CA.

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


@ThingsExpo Stories
Hadoop as a Service (as offered by handful of niche vendors now) is a cloud computing solution that makes medium and large-scale data processing accessible, easy, fast and inexpensive. In his session at Big Data Expo, Kumar Ramamurthy, Vice President and Chief Technologist, EIM & Big Data, at Virtusa, will discuss how this is achieved by eliminating the operational challenges of running Hadoop, so one can focus on business growth. The fragmented Hadoop distribution world and various PaaS solutions that provide a Hadoop flavor either make choices for customers very flexible in the name of opti...
Even as cloud and managed services grow increasingly central to business strategy and performance, challenges remain. The biggest sticking point for companies seeking to capitalize on the cloud is data security. Keeping data safe is an issue in any computing environment, and it has been a focus since the earliest days of the cloud revolution. Understandably so: a lot can go wrong when you allow valuable information to live outside the firewall. Recent revelations about government snooping, along with a steady stream of well-publicized data breaches, only add to the uncertainty
The Workspace-as-a-Service (WaaS) market will grow to $6.4B by 2018. In his session at 16th Cloud Expo, Seth Bostock, CEO of IndependenceIT, will begin by walking the audience through the evolution of Workspace as-a-Service, where it is now vs. where it going. To look beyond the desktop we must understand exactly what WaaS is, who the users are, and where it is going in the future. IT departments, ISVs and service providers must look to workflow and automation capabilities to adapt to growing demand and the rapidly changing workspace model.
SYS-CON Events announced today that Dyn, the worldwide leader in Internet Performance, will exhibit at SYS-CON's 16th International Cloud Expo®, which will take place on June 9-11, 2015, at the Javits Center in New York City, NY. Dyn is a cloud-based Internet Performance company. Dyn helps companies monitor, control, and optimize online infrastructure for an exceptional end-user experience. Through a world-class network and unrivaled, objective intelligence into Internet conditions, Dyn ensures traffic gets delivered faster, safer, and more reliably than ever.
As organizations shift toward IT-as-a-service models, the need for managing and protecting data residing across physical, virtual, and now cloud environments grows with it. CommVault can ensure protection &E-Discovery of your data – whether in a private cloud, a Service Provider delivered public cloud, or a hybrid cloud environment – across the heterogeneous enterprise. In his session at 16th Cloud Expo, Randy De Meno, Chief Technologist - Windows Products and Microsoft Partnerships, will discuss how to cut costs, scale easily, and unleash insight with CommVault Simpana software, the only si...
Cloud data governance was previously an avoided function when cloud deployments were relatively small. With the rapid adoption in public cloud – both rogue and sanctioned, it’s not uncommon to find regulated data dumped into public cloud and unprotected. This is why enterprises and cloud providers alike need to embrace a cloud data governance function and map policies, processes and technology controls accordingly. In her session at 15th Cloud Expo, Evelyn de Souza, Data Privacy and Compliance Strategy Leader at Cisco Systems, will focus on how to set up a cloud data governance program and s...
Roberto Medrano, Executive Vice President at SOA Software, had reached 30,000 page views on his home page - http://RobertoMedrano.SYS-CON.com/ - on the SYS-CON family of online magazines, which includes Cloud Computing Journal, Internet of Things Journal, Big Data Journal, and SOA World Magazine. He is a recognized executive in the information technology fields of SOA, internet security, governance, and compliance. He has extensive experience with both start-ups and large companies, having been involved at the beginning of four IT industries: EDA, Open Systems, Computer Security and now SOA.
The industrial software market has treated data with the mentality of “collect everything now, worry about how to use it later.” We now find ourselves buried in data, with the pervasive connectivity of the (Industrial) Internet of Things only piling on more numbers. There’s too much data and not enough information. In his session at @ThingsExpo, Bob Gates, Global Marketing Director, GE’s Intelligent Platforms business, to discuss how realizing the power of IoT, software developers are now focused on understanding how industrial data can create intelligence for industrial operations. Imagine ...
Operational Hadoop and the Lambda Architecture for Streaming Data Apache Hadoop is emerging as a distributed platform for handling large and fast incoming streams of data. Predictive maintenance, supply chain optimization, and Internet-of-Things analysis are examples where Hadoop provides the scalable storage, processing, and analytics platform to gain meaningful insights from granular data that is typically only valuable from a large-scale, aggregate view. One architecture useful for capturing and analyzing streaming data is the Lambda Architecture, representing a model of how to analyze rea...
SYS-CON Events announced today that Vitria Technology, Inc. will exhibit at SYS-CON’s @ThingsExpo, which will take place on June 9-11, 2015, at the Javits Center in New York City, NY. Vitria will showcase the company’s new IoT Analytics Platform through live demonstrations at booth #330. Vitria’s IoT Analytics Platform, fully integrated and powered by an operational intelligence engine, enables customers to rapidly build and operationalize advanced analytics to deliver timely business outcomes for use cases across the industrial, enterprise, and consumer segments.
The Internet of Things (IoT) promises to evolve the way the world does business; however, understanding how to apply it to your company can be a mystery. Most people struggle with understanding the potential business uses or tend to get caught up in the technology, resulting in solutions that fail to meet even minimum business goals. In his session at @ThingsExpo, Jesse Shiah, CEO / President / Co-Founder of AgilePoint Inc., showed what is needed to leverage the IoT to transform your business. He discussed opportunities and challenges ahead for the IoT from a market and technical point of vie...
Advanced Persistent Threats (APTs) are increasing at an unprecedented rate. The threat landscape of today is drastically different than just a few years ago. Attacks are much more organized and sophisticated. They are harder to detect and even harder to anticipate. In the foreseeable future it's going to get a whole lot harder. Everything you know today will change. Keeping up with this changing landscape is already a daunting task. Your organization needs to use the latest tools, methods and expertise to guard against those threats. But will that be enough? In the foreseeable future attacks w...
HP and Aruba Networks on Monday announced a definitive agreement for HP to acquire Aruba, a provider of next-generation network access solutions for the mobile enterprise, for $24.67 per share in cash. The equity value of the transaction is approximately $3.0 billion, and net of cash and debt approximately $2.7 billion. Both companies' boards of directors have approved the deal. "Enterprises are facing a mobile-first world and are looking for solutions that help them transition legacy investments to the new style of IT," said Meg Whitman, Chairman, President and Chief Executive Officer of HP...
Containers and microservices have become topics of intense interest throughout the cloud developer and enterprise IT communities. Accordingly, attendees at the upcoming 16th Cloud Expo at the Javits Center in New York June 9-11 will find fresh new content in a new track called PaaS | Containers & Microservices Containers are not being considered for the first time by the cloud community, but a current era of re-consideration has pushed them to the top of the cloud agenda. With the launch of Docker's initial release in March of 2013, interest was revved up several notches. Then late last...
Disruptive macro trends in technology are impacting and dramatically changing the "art of the possible" relative to supply chain management practices through the innovative use of IoT, cloud, machine learning and Big Data to enable connected ecosystems of engagement. Enterprise informatics can now move beyond point solutions that merely monitor the past and implement integrated enterprise fabrics that enable end-to-end supply chain visibility to improve customer service delivery and optimize supplier management. Learn about enterprise architecture strategies for designing connected systems tha...
The explosion of connected devices / sensors is creating an ever-expanding set of new and valuable data. In parallel the emerging capability of Big Data technologies to store, access, analyze, and react to this data is producing changes in business models under the umbrella of the Internet of Things (IoT). In particular within the Insurance industry, IoT appears positioned to enable deep changes by altering relationships between insurers, distributors, and the insured. In his session at @ThingsExpo, Michael Sick, a Senior Manager and Big Data Architect within Ernst and Young's Financial Servi...
The explosion of connected devices / sensors is creating an ever-expanding set of new and valuable data. In parallel the emerging capability of Big Data technologies to store, access, analyze, and react to this data is producing changes in business models under the umbrella of the Internet of Things (IoT). In particular within the Insurance industry, IoT appears positioned to enable deep changes by altering relationships between insurers, distributors, and the insured. In his session at @ThingsExpo, Michael Sick, a Senior Manager and Big Data Architect within Ernst and Young's Financial Servi...
PubNub on Monday has announced that it is partnering with IBM to bring its sophisticated real-time data streaming and messaging capabilities to Bluemix, IBM’s cloud development platform. “Today’s app and connected devices require an always-on connection, but building a secure, scalable solution from the ground up is time consuming, resource intensive, and error-prone,” said Todd Greene, CEO of PubNub. “PubNub enables web, mobile and IoT developers building apps on IBM Bluemix to quickly add scalable realtime functionality with minimal effort and cost.”
Sensor-enabled things are becoming more commonplace, precursors to a larger and more complex framework that most consider the ultimate promise of the IoT: things connecting, interacting, sharing, storing, and over time perhaps learning and predicting based on habits, behaviors, location, preferences, purchases and more. In his session at @ThingsExpo, Tom Wesselman, Director of Communications Ecosystem Architecture at Plantronics, will examine the still nascent IoT as it is coalescing, including what it is today, what it might ultimately be, the role of wearable tech, and technology gaps stil...
With several hundred implementations of IoT-enabled solutions in the past 12 months alone, this session will focus on experience over the art of the possible. Many can only imagine the most advanced telematics platform ever deployed, supporting millions of customers, producing tens of thousands events or GBs per trip, and hundreds of TBs per month. With the ability to support a billion sensor events per second, over 30PB of warm data for analytics, and hundreds of PBs for an data analytics archive, in his session at @ThingsExpo, Jim Kaskade, Vice President and General Manager, Big Data & Ana...