Click here to close now.

Welcome!

.NET Authors: Carmen Gonzalez, Elizabeth White, Liz McMillan, Greg O'Connor, Jason Bloomberg

Related Topics: Microservices Journal

Microservices Journal: Article

In-Memory BI Is Not the Future, It’s the Past

Why the current in-memory BI hype can be misleading.

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:

Disk RAM
Abundant Scarce
Slower Faster
Cheap Expensive
Long-term Short-term

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.’

Disk-based BI
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 BI
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.

More Stories By Elad Israeli

Elad Israeli is co-founder of business intelligence software company, SiSense. SiSense has developed Prism, a next-generation business intelligence platform based on its own, unique ElastiCube BI technology. Elad is responsible for driving the vision and strategy of SiSense’s unique BI products. Before co-founding SiSense, Elad served as a Product Manager at global IT services firm Ness Technologies (NASDAQ: NSTC). Previously, Elad was a Product Manager at Anysoft and, before that, he co-founded and led technology development at BiSense, a BI technology company.

@ThingsExpo Stories
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...
The best mobile applications are augmented by dedicated servers, the Internet and Cloud services. Mobile developers should focus on one thing: writing the next socially disruptive viral app. Thanks to the cloud, they can focus on the overall solution, not the underlying plumbing. From iOS to Android and Windows, developers can leverage cloud services to create a common cross-platform backend to persist user settings, app data, broadcast notifications, run jobs, etc. This session provides a high level technical overview of many cloud services available to mobile app developers, includi...
“In the past year we've seen a lot of stabilization of WebRTC. You can now use it in production with a far greater degree of certainty. A lot of the real developments in the past year have been in things like the data channel, which will enable a whole new type of application," explained Peter Dunkley, Technical Director at Acision, in this SYS-CON.tv interview at @ThingsExpo, held Nov 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA.
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...
Health care systems across the globe are under enormous strain, as facilities reach capacity and costs continue to rise. M2M and the Internet of Things have the potential to transform the industry through connected health solutions that can make care more efficient while reducing costs. In fact, Vodafone's annual M2M Barometer Report forecasts M2M applications rising to 57 percent in health care and life sciences by 2016. Lively is one of Vodafone's health care partners, whose solutions enable older adults to live independent lives while staying connected to loved ones. M2M will continue to gr...
SYS-CON Events announced today that Ciqada 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. Ciqada™ makes it easy to connect your products to the Internet. By integrating key components - hardware, servers, dashboards, and mobile apps - into an easy-to-use, configurable system, your products can quickly and securely join the internet of things. With remote monitoring, control, and alert messaging capability, you will meet your customers' needs of tomorrow - today! Ciqada. Let your products take flight. For more inform...
Dave will share his insights on how Internet of Things for Enterprises are transforming and making more productive and efficient operations and maintenance (O&M) procedures in the cleantech industry and beyond. Speaker Bio: Dave Landa is chief operating officer of Cybozu Corp (kintone US). Based in the San Francisco Bay Area, Dave has been on the forefront of the Cloud revolution driving strategic business development on the executive teams of multiple leading Software as a Services (SaaS) application providers dating back to 2004. Cybozu's kintone.com is a leading global BYOA (Build Your O...
While not quite mainstream yet, WebRTC is starting to gain ground with Carriers, Enterprises and Independent Software Vendors (ISV’s) alike. WebRTC makes it easy for developers to add audio and video communications into their applications by using Web browsers as their platform. But like any market, every customer engagement has unique requirements, as well as constraints. And of course, one size does not fit all. In her session at WebRTC Summit, Dr. Natasha Tamaskar, Vice President, Head of Cloud and Mobile Strategy at GENBAND, will explore what is needed to take a real time communications ...
SYS-CON Media announced today that @WebRTCSummit Blog, the largest WebRTC resource in the world, has been launched. @WebRTCSummit Blog offers top articles, news stories, and blog posts from the world's well-known experts and guarantees better exposure for its authors than any other publication. @WebRTCSummit Blog can be bookmarked ▸ Here @WebRTCSummit conference site can be bookmarked ▸ Here
SYS-CON Events announced today that GENBAND, a leading developer of real time communications software solutions, has been named “Silver Sponsor” of SYS-CON's WebRTC Summit, which will take place on June 9-11, 2015, at the Javits Center in New York City, NY. The GENBAND team will be on hand to demonstrate their newest product, Kandy. Kandy is a communications Platform-as-a-Service (PaaS) that enables companies to seamlessly integrate more human communications into their Web and mobile applications - creating more engaging experiences for their customers and boosting collaboration and productiv...
SYS-CON Events announced today that BroadSoft, the leading global provider of Unified Communications and Collaboration (UCC) services to operators worldwide, has been named “Gold Sponsor” of SYS-CON's WebRTC Summit, which will take place on June 9-11, 2015, at the Javits Center in New York City, NY. BroadSoft is the leading provider of software and services that enable mobile, fixed-line and cable service providers to offer Unified Communications over their Internet Protocol networks. The Company’s core communications platform enables the delivery of a range of enterprise and consumer calling...
What exactly is a cognitive application? In her session at 16th Cloud Expo, Ashley Hathaway, Product Manager at IBM Watson, will look at the services being offered by the IBM Watson Developer Cloud and what that means for developers and Big Data. She'll explore how IBM Watson and its partnerships will continue to grow and help define what it means to be a cognitive service, as well as take a look at the offerings on Bluemix. She will also check out how Watson and the Alchemy API team up to offer disruptive APIs to developers.
The IoT Bootcamp is coming to Cloud Expo | @ThingsExpo on June 9-10 at the Javits Center in New York. Instructor. Registration is now available at http://iotbootcamp.sys-con.com/ Instructor Janakiram MSV previously taught the famously successful Multi-Cloud Bootcamp at Cloud Expo | @ThingsExpo in November in Santa Clara. Now he is expanding the focus to Janakiram is the founder and CTO of Get Cloud Ready Consulting, a niche Cloud Migration and Cloud Operations firm that recently got acquired by Aditi Technologies. He is a Microsoft Regional Director for Hyderabad, India, and one of the f...
The 17th International Cloud Expo has announced that its Call for Papers is open. 17th International Cloud Expo, to be held November 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA, brings together Cloud Computing, APM, APIs, Microservices, Security, Big Data, Internet of Things, DevOps and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding business opportunity. Submit your speaking proposal today!
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...
SYS-CON Events announced today that robomq.io 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. robomq.io is an interoperable and composable platform that connects any device to any application. It helps systems integrators and the solution providers build new and innovative products and service for industries requiring monitoring or intelligence from devices and sensors.
Wearable technology was dominant at this year’s International Consumer Electronics Show (CES) , and MWC was no exception to this trend. New versions of favorites, such as the Samsung Gear (three new products were released: the Gear 2, the Gear 2 Neo and the Gear Fit), shared the limelight with new wearables like Pebble Time Steel (the new premium version of the company’s previously released smartwatch) and the LG Watch Urbane. The most dramatic difference at MWC was an emphasis on presenting wearables as fashion accessories and moving away from the original clunky technology associated with t...
SYS-CON Events announced today that Litmus Automation 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. Litmus Automation’s vision is to provide a solution for companies that are in a rush to embrace the disruptive Internet of Things technology and leverage it for real business challenges. Litmus Automation simplifies the complexity of connected devices applications with Loop, a secure and scalable cloud platform.
In 2015, 4.9 billion connected "things" will be in use. By 2020, Gartner forecasts this amount to be 25 billion, a 410 percent increase in just five years. How will businesses handle this rapid growth of data? Hadoop will continue to improve its technology to meet business demands, by enabling businesses to access/analyze data in real time, when and where they need it. Cloudera's Chief Technologist, Eli Collins, will discuss how Big Data is keeping up with today's data demands and how in the future, data and analytics will be pervasive, embedded into every workflow, application and infra...
As Marc Andreessen says software is eating the world. Everything is rapidly moving toward being software-defined – from our phones and cars through our washing machines to the datacenter. However, there are larger challenges when implementing software defined on a larger scale - when building software defined infrastructure. In his session at 16th Cloud Expo, Boyan Ivanov, CEO of StorPool, will provide some practical insights on what, how and why when implementing "software-defined" in the datacenter.