|By Elad Israeli||
|October 7, 2010 10:25 AM EDT||
In recent times, one of the most popular subjects related to the field of Business Intelligence (BI) has been In-memory BI technology. The subject gained popularity largely due to the success of QlikTech, provider of the in-memory-based QlikView BI product. Following QlikTech’s lead, many other BI vendors have jumped on the in-memory “hype wagon,” including the software giant, Microsoft, which has been aggressively marketing PowerPivot, their own in-memory database engine.
The increasing hype surrounding in-memory BI has caused BI consultants, analysts and even vendors to spew out endless articles, blog posts and white papers on the subject, many of which have also gone the extra mile to describe in-memory technology as the future of business intelligence, the death blow to the data warehouse and the swan song of OLAP technology. I find one of these in my inbox every couple of weeks.
Just so it is clear - the concept of in-memory business intelligence is not new. It has been around for many years. The only reason it became widely known recently is because it wasn’t feasible before 64-bit computing became commonly available. Before 64-bit processors, the maximum amount of RAM a computer could utilize was barely 4GB, which is hardly enough to accommodate even the simplest of multi-user BI solutions. Only when 64-bit systems became cheap enough did it became possible to consider in-memory technology as a practical option for BI.
The success of QlikTech and the relentless activities of Microsoft’s marketing machine have managed to confuse many in terms of what role in-memory technology plays in BI implementations. And that is why many of the articles out there, which are written by marketers or market analysts who are not proficient in the internal workings of database technology (and assume their readers aren’t either), are usually filled with inaccuracies and, in many cases, pure nonsense.
The purpose of this article is to put both in-memory and disk-based BI technologies in perspective, explain the differences between them and finally lay out, in simple terms, why disk-based BI technology isn’t on its way to extinction. Rather, disk-based BI technology is evolving into something that will significantly limit the use of in-memory technology in typical BI implementations.
But before we get to that, for the sake of those who are not very familiar with in-memory BI technology, here’s a brief introduction to the topic.
Disk and RAM
Generally speaking, your computer has two types of data storage mechanisms – disk (often called a hard disk) and RAM (random access memory). The important differences between them (for this discussion) are outlined in the following table:
Most modern computers have 15-100 times more available disk storage than they do RAM. My laptop, for example, has 8GB of RAM and 300GB of available disk space. However, reading data from disk is much slower than reading the same data from RAM. This is one of the reasons why 1GB of RAM costs approximately 320 times that of 1GB of disk space.
Another important distinction is what happens to the data when the computer is powered down: data stored on disk is unaffected (which is why your saved documents are still there the next time you turn on your computer), but data residing in RAM is instantly lost. So, while you don’t have to re-create your disk-stored Microsoft Word documents after a reboot, you do have to re-load the operating system, re-launch the word processor and reload your document. This is because applications and their internal data are partly, if not entirely, stored in RAM while they are running.
Disk-based Databases and In-memory Databases
Now that we have a general idea of what the basic differences between disk and RAM are, what are the differences between disk-based and in-memory databases? Well, all data is always kept on hard disks (so that they are saved even when the power goes down). When we talk about whether a database is disk-based or in-memory, we are talking about where the data resides while it is actively being queried by an application: with disk-based databases, the data is queried while stored on disk and with in-memory databases, the data being queried is first loaded into RAM.
Disk-based databases are engineered to efficiently query data residing on the hard drive. At a very basic level, these databases assume that the entire data cannot fit inside the relatively small amount of RAM available and therefore must have very efficient disk reads in order for queries to be returned within a reasonable time frame. The engineers of such databases have the benefit of unlimited storage, but must face the challenges of relying on relatively slow disk operations.
On the other hand, in-memory databases work under the opposite assumption that the data can, in fact, fit entirely inside the RAM. The engineers of in-memory databases benefit from utilizing the fastest storage system a computer has (RAM), but have much less of it at their disposal.
That is the fundamental trade-off in disk-based and in-memory technologies: faster reads and limited amounts of data versus slower reads and practically unlimited amounts of data. These are two critical considerations for business intelligence applications, as it is important both to have fast query response times and to have access to as much data as possible.
The Data Challenge
A business intelligence solution (almost) always has a single data store at its center. This data store is usually called a database, data warehouse, data mart or OLAP cube. This is where the data that can be queried by the BI application is stored.
The challenges in creating this data store using traditional disk-based technologies is what gave in-memory technology its 15 minutes (ok, maybe 30 minutes) of fame. Having the entire data model stored inside RAM allowed bypassing some of the challenges encountered by their disk-based counterparts, namely the issue of query response times or ‘slow queries.’
When saying ‘traditional disk-based’ technologies, we typically mean relational database management systems (RDBMS) such as SQL Server, Oracle, MySQL and many others. It’s true that having a BI solution perform well using these types of databases as their backbone is far more challenging than simply shoving the entire data model into RAM, where performance gains would be immediate due to the fact RAM is so much faster than disk.
It’s commonly thought that relational databases are too slow for BI queries over data in (or close to) its raw form due to the fact they are disk-based. The truth is, however, that it’s because of how they use the disk and how often they use it.
Relational databases were designed with transactional processing in mind. But having a database be able to support high-performance insertions and updates of transactions (i.e., rows in a table) as well as properly accommodating the types of queries typically executed in BI solutions (e.g., aggregating, grouping, joining) is impossible. These are two mutually-exclusive engineering goals, that is to say they require completely different architectures at the very core. You simply can’t use the same approach to ideally achieve both.
In addition, the standard query language used to extract transactions from relational databases (SQL) is syntactically designed for the efficient fetching of rows, while rare are the cases in BI where you would need to scan or retrieve an entire row of data. It is nearly impossible to formulate an efficient BI query using SQL syntax.
So while relational databases are great as the backbone of operational applications such as CRM, ERP or Web sites, where transactions are frequently and simultaneously inserted, they are a poor choice for supporting analytic applications which usually involve simultaneous retrieval of partial rows along with heavy calculations.
In-memory databases approach the querying problem by loading the entire dataset into RAM. In so doing, they remove the need to access the disk to run queries, thus gaining an immediate and substantial performance advantage (simply because scanning data in RAM is orders of magnitude faster than reading it from disk). Some of these databases introduce additional optimizations which further improve performance. Most of them also employ compression techniques to represent even more data in the same amount of RAM.
Regardless of what fancy footwork is used with an in-memory database, storing the entire dataset in RAM has a serious implication: the amount of data you can query with in-memory technology is limited by the amount of free RAM available, and there will always be much less available RAM than available disk space.
The bottom line is that this limited memory space means that the quality and effectiveness of your BI application will be hindered: the more historical data to which you have access and/or the more fields you can query, the better analysis, insight and, well, intelligence you can get.
You could add more and more RAM, but then the hardware you require becomes exponentially more expensive. The fact that 64-bit computers are cheap and can theoretically support unlimited amounts of RAM does not mean they actually do in practice. A standard desktop-class (read: cheap) computer with standard hardware physically supports up to 12GB of RAM today. If you need more, you can move on to a different class of computer which costs about twice as much and will allow you up to 64GB. Beyond 64GB, you can no longer use what is categorized as a personal computer but will require a full-blown server which brings you into very expensive computing territory.
It is also important to understand that the amount of RAM you need is not only affected by the amount of data you have, but also by the number of people simultaneously querying it. Having 5-10 people using the same in-memory BI application could easily double the amount of RAM required for intermediate calculations that need to be performed to generate the query results. A key success factor in most BI solutions is having a large number of users, so you need to tread carefully when considering in-memory technology for real-world BI. Otherwise, your hardware costs may spiral beyond what you are willing or able to spend (today, or in the future as your needs increase).
There are other implications to having your data model stored in memory, such as having to re-load it from disk to RAM every time the computer reboots and not being able to use the computer for anything other than the particular data model you’re using because its RAM is all used up.
A Note about QlikView and PowerPivot In-memory Technologies
QlikTech is the most active in-memory BI player out there so their QlikView in-memory technology is worth addressing in its own right. It has been repeatedly described as “unique, patented associative technology” but, in fact, there is nothing “associative” about QlikView’s in-memory technology. QlikView uses a simple tabular data model, stored entirely in-memory, with basic token-based compression applied to it. In QlikView’s case, the word associative relates to the functionality of its user interface, not how the data model is physically stored. Associative databases are a completely different beast and have nothing in common with QlikView’s technology.
PowerPivot uses a similar concept, but is engineered somewhat differently due to the fact it’s meant to be used largely within Excel. In this respect, PowerPivot relies on a columnar approach to storage that is better suited for the types of calculations conducted in Excel 2010, as well as for compression. Quality of compression is a significant differentiator between in-memory technologies as better compression means that you can store more data in the same amount RAM (i.e., more data is available for users to query). In its current version, however, PowerPivot is still very limited in the amounts of data it supports and requires a ridiculous amount of RAM.
The Present and Future Technologies
The destiny of BI lies in technologies that leverage the respective benefits of both disk-based and in-memory technologies to deliver fast query responses and extensive multi-user access without monstrous hardware requirements. Obviously, these technologies cannot be based on relational databases, but they must also not be designed to assume a massive amount of RAM, which is a very scarce resource.
These types of technologies are not theoretical anymore and are already utilized by businesses worldwide. Some are designed to distribute different portions of complex queries across multiple cheaper computers (this is a good option for cloud-based BI systems) and some are designed to take advantage of 21st-century hardware (multi-core architectures, upgraded CPU cache sizes, etc.) to extract more juice from off-the-shelf computers.
A Final Note: ElastiCube Technology
The technology developed by the company I co-founded, SiSense, belongs to the latter category. That is, SiSense utilizes technology which combines the best of disk-based and in-memory solutions, essentially eliminating the downsides of each. SiSense’s BI product, Prism, enables a standard PC to deliver a much wider variety of BI solutions, even when very large amounts of data, large numbers of users and/or large numbers of data sources are involved, as is the case in typical BI projects.
When we began our research at SiSense, our technological assumption was that it is possible to achieve in-memory-class query response times, even for hundreds of users simultaneously accessing massive data sets, while keeping the data (mostly) stored on disk. The result of our hybrid disk-based/in-memory technology is a BI solution based on what we now call ElastiCube, after which this blog is named. You can read more about this technological approach, which we call Just-in-Time In-memory Processing, at our BI Software Evolved technology page.
SYS-CON Events announced today the IoT Bootcamp – Jumpstart Your IoT Strategy, being held June 9–10, 2015, in conjunction with 16th Cloud Expo and Internet of @ThingsExpo at the Javits Center in New York City. This is your chance to jumpstart your IoT strategy. Combined with real-world scenarios and use cases, the IoT Bootcamp is not just based on presentations but includes hands-on demos and walkthroughs. We will introduce you to a variety of Do-It-Yourself IoT platforms including Arduino, Raspberry Pi, BeagleBone, Spark and Intel Edison. You will also get an overview of cloud technologies s...
Apr. 25, 2015 10:15 AM EDT Reads: 2,981
The only place to be June 9-11 is Cloud Expo & @ThingsExpo 2015 East at the Javits Center in New York City. Join us there as delegates from all over the world come to listen to and engage with speakers & sponsors from the leading Cloud Computing, IoT & Big Data companies. Cloud Expo & @ThingsExpo are the leading events covering the booming market of Cloud Computing, IoT & Big Data for the enterprise. Speakers from all over the world will be hand-picked for their ability to explore the economic strategies that utility/cloud computing provides. Whether public, private, or in a hybrid form, clo...
Apr. 25, 2015 10:00 AM EDT Reads: 4,151
WebRTC is an up-and-coming standard that enables real-time voice and video to be directly embedded into browsers making the browser a primary user interface for communications and collaboration. WebRTC runs in a number of browsers today and is currently supported in over a billion installed browsers globally, across a range of platform OS and devices. Today, organizations that choose to deploy WebRTC applications and use a host machine that supports audio through USB or Bluetooth can use Plantronics products to connect and transit or receive the audio associated with the WebRTC session.
Apr. 25, 2015 10:00 AM EDT Reads: 1,867
Internet of Things (IoT) will be a hybrid ecosystem of diverse devices and sensors collaborating with operational and enterprise systems to create the next big application. In their session at @ThingsExpo, Bramh Gupta, founder and CEO of robomq.io, and Fred Yatzeck, principal architect leading product development at robomq.io, will discuss how choosing the right middleware and integration strategy from the get-go will enable IoT solution developers to adapt and grow with the industry, while at the same time reduce Time to Market (TTM) by using plug and play capabilities offered by a robust I...
Apr. 25, 2015 10:00 AM EDT Reads: 1,955
IoT is still a vague buzzword for many people. In his session at @ThingsExpo, Mike Kavis, Vice President & Principal Cloud Architect at Cloud Technology Partners, discussed the business value of IoT that goes far beyond the general public's perception that IoT is all about wearables and home consumer services. He also discussed how IoT is perceived by investors and how venture capitalist access this space. Other topics discussed were barriers to success, what is new, what is old, and what the future may hold. Mike Kavis is Vice President & Principal Cloud Architect at Cloud Technology Pa...
Apr. 25, 2015 10:00 AM EDT Reads: 6,152
@ThingsExpo has been named the Top 5 Most Influential Internet of Things Brand by Onalytica in the ‘The Internet of Things Landscape 2015: Top 100 Individuals and Brands.' Onalytica analyzed Twitter conversations around the #IoT debate to uncover the most influential brands and individuals driving the conversation. Onalytica captured data from 56,224 users. The PageRank based methodology they use to extract influencers on a particular topic (tweets mentioning #InternetofThings or #IoT in this case) takes into account the number and quality of contextual references that a user receives.
Apr. 25, 2015 10:00 AM EDT Reads: 1,986
Buzzword alert: Microservices and IoT at a DevOps conference? What could possibly go wrong? Join this panel of experts as they peel away the buzz and discuss the important architectural principles behind implementing IoT solutions for the enterprise. As remote IoT devices and sensors become increasingly intelligent, they become part of our distributed cloud environment, and we must architect and code accordingly. At the very least, you’ll have no problem filling in your buzzword bingo cards.
Apr. 25, 2015 10:00 AM EDT Reads: 2,191
So I guess we’ve officially entered a new era of lean and mean. I say this with the announcement of Ubuntu Snappy Core, “designed for lightweight cloud container hosts running Docker and for smart devices,” according to Canonical. “Snappy Ubuntu Core is the smallest Ubuntu available, designed for security and efficiency in devices or on the cloud.” This first version of Snappy Ubuntu Core features secure app containment and Docker 1.6 (1.5 in main release), is available on public clouds, and for ARM and x86 devices on several IoT boards. It’s a Trend! This announcement comes just as...
Apr. 25, 2015 10:00 AM EDT Reads: 1,346
SYS-CON Events announced today that AIC, a leading provider of OEM/ODM server and storage solutions, 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. AIC is a leading provider of both standard OTS, off-the-shelf, and OEM/ODM server and storage solutions. With expert in-house design capabilities, validation, manufacturing and production, AIC's broad selection of products are highly flexible and are configurable to any form factor or custom configuration. AIC leads the industry with nearly 20 years of ...
Apr. 25, 2015 10:00 AM EDT Reads: 4,910
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...
Apr. 25, 2015 10:00 AM EDT Reads: 2,808
As enterprises move to all-IP networks and cloud-based applications, communications service providers (CSPs) – facing increased competition from over-the-top providers delivering content via the Internet and independently of CSPs – must be able to offer seamless cloud-based communication and collaboration solutions that can scale for small, midsize, and large enterprises, as well as public sector organizations, in order to keep and grow market share. The latest version of Oracle Communications Unified Communications Suite gives CSPs the capability to do just that. In addition, its integration ...
Apr. 25, 2015 09:30 AM EDT Reads: 4,338
SYS-CON Events announced today that Creative Business Solutions 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. Creative Business Solutions is the top stocking authorized HP Renew Distributor in the U.S. Based out of Long Island, NY, Creative Business Solutions offers a one-stop shop for a diverse range of products including Proliant, Blade and Industry Standard Servers, Networking, Server Options and Care Packs. As a trusted supplier, CBS guarantees quality controlled stock levels thanks to an Auto...
Apr. 25, 2015 09:15 AM EDT Reads: 4,338
SOA Software has changed its name to Akana. With roots in Web Services and SOA Governance, Akana has established itself as a leader in API Management and is expanding into cloud integration as an alternative to the traditional heavyweight enterprise service bus (ESB). The company recently announced that it achieved more than 90% year-over-year growth. As Akana, the company now addresses the evolution and diversification of SOA, unifying security, management, and DevOps across SOA, APIs, microservices, and more.
Apr. 25, 2015 09:15 AM EDT Reads: 2,395
GENBAND introduced its Real Time Communications (RTC) Client for Lync* to seamlessly combine real-time communications with Lync Instant Messaging (IM) and Presence. “We’re shaking up the economics of delivering Unified Communications (UC) and offering a compelling way to integrate previously bespoke communications technologies,” said Carl Baptiste, GENBAND’s Senior Vice President, Enterprise Solutions. “We’re offering enterprises the best of both worlds by combining our own high availability voice, video and collaboration with Lync’s IM and Presence; creating a single, web centric, client. O...
Apr. 25, 2015 09:00 AM EDT Reads: 1,679
After making a doctor’s appointment via your mobile device, you receive a calendar invite. The day of your appointment, you get a reminder with the doctor’s location and contact information. As you enter the doctor’s exam room, the medical team is equipped with the latest tablet containing your medical history – he or she makes real time updates to your medical file. At the end of your visit, you receive an electronic prescription to your preferred pharmacy and can schedule your next appointment.
Apr. 25, 2015 09:00 AM EDT Reads: 1,424
From telemedicine to smart cars, digital homes and industrial monitoring, the explosive growth of IoT has created exciting new business opportunities for real time calls and messaging. In his session at @ThingsExpo, Ivelin Ivanov, CEO and Co-Founder of Telestax, shared some of the new revenue sources that IoT created for Restcomm – the open source telephony platform from Telestax. Ivelin Ivanov is a technology entrepreneur who founded Mobicents, an Open Source VoIP Platform, to help create, deploy, and manage applications integrating voice, video and data. He is the co-founder of TeleStax, a...
Apr. 25, 2015 09:00 AM EDT Reads: 5,139
Can call centers hang up the phones for good? Intuitive Solutions did. WebRTC enabled this contact center provider to eliminate antiquated telephony and desktop phone infrastructure with a pure web-based solution, allowing them to expand beyond brick-and-mortar confines to a home-based agent model. It also ensured scalability and better service for customers, including MUY! Companies, one of the country's largest franchise restaurant companies with 232 Pizza Hut locations. This is one example of WebRTC adoption today, but the potential is limitless when powered by IoT.
Apr. 25, 2015 09:00 AM EDT Reads: 5,266
SYS-CON Events announced today that Optimal Design, an Internet of Things solution provider, will exhibit at SYS-CON's Internet of @ThingsExpo, which will take place on June 9-11, 2015, at the Javits Center in New York City, NY. Optimal Design is an award winning product development firm offering industrial design and engineering services to the consumer, medical, and defense markets.
Apr. 25, 2015 09:00 AM EDT Reads: 1,674
How is unified communications transforming the way businesses operate? In his session at WebRTC Summit, Arvind Rangarajan, Director of Product Marketing at BroadSoft, will discuss how to extend unified communications experience outside the enterprise through WebRTC. He will also review use cases across different industry verticals. Arvind Rangarajan is Director, Product Marketing at BroadSoft. He has over 19 years of experience in the telecommunications industry in various roles such as Software Development, Product Management and Product Marketing, applied across Wireless, Unified Communic...
Apr. 25, 2015 09:00 AM EDT Reads: 1,704
The list of ‘new paradigm’ technologies that now surrounds us appears to be at an all time high. From cloud computing and Big Data analytics to Bring Your Own Device (BYOD) and the Internet of Things (IoT), today we have to deal with what the industry likes to call ‘paradigm shifts’ at every level of IT. This is disruption; of course, we understand that – change is almost always disruptive.
Apr. 25, 2015 09:00 AM EDT Reads: 1,515