|By Elad Israeli||
|October 20, 2010 03:13 PM EDT||
OLAP (Online Analytical Processing) technology is the most prevalent technology used in corporate BI solutions today. And while it does what it’s supposed to do very well, it has a bad (and accurate) reputation for being very expensive and difficult to implement, as well as extremely challenging to maintain. This fact has prevented OLAP technology from gaining wide popularity outside of Fortune 500-scale companies, which are the only ones who have the budgets for company-wide, OLAP-based BI implementations.
The most recently recognized innovation (even though it’s been around for quite a while) was in-memory technology, whose main advantage was cutting implementation time and simplifying the process as a whole (a definite step in the right direction). However, as described in my recent article, In-Memory BI is Not the Future, It's the Past, using in-memory technology for speedy BI implementation introduces significant compromises, especially in terms of scalability (both for data volumes and support for many concurrent users). Now, after in-memory technology has been on the market for some time, it is clear that it is not really a replacement for OLAP technology, but did in fact expand the BI market to a wider audience. In fact, it is probably more accurate to say that in-memory technology and OLAP technology complement each other, each with its own advantages and tradeoffs.
In that article I also briefly mentioned the new disk-based ElastiCube technology (invented by SiSense). ElastiCube technology basically eliminates the inherent IMDB tradeoffs by providing unlimited scalability using off-the-shelf hardware while delivering both implementation and query response times as fast (or faster) as pure in-memory-based solutions. This claim was the subject of many of the emails and inquires I received following the article’s publication. I was repeatedly asked how ElastiCube technology had achieved what OLAP technology had failed to do for so many years, and what role in-memory technology played in its conception.
Thus, in this article I will describe how ElastiCube technology came to be, what inspired it, what made it possible and how it has already become a game-changer in the BI space, both in large corporations and small startups.
A Brief History of BI and OLAP
OLAP technology started gaining popularity in the late 1990s, and that had a lot to do with Microsoft’s first release of their OLAP Services product (now Analysis Services), based on technology acquired from Panorama Software. At that point in time, computer hardware wasn’t nearly as powerful as it is today; given the circumstances at the time, OLAP was groundbreaking. It introduced a spectacular way for business users (typically analysts) to easily perform multidimensional analysis of large volumes of business data. When Microsoft’s Multidimensional Expressions language (MDX) came closer to becoming a standard, more and more client tools (e.g., Panorama NovaView, ProClarity) started popping up to provide even more power to these users.
While Microsoft was not the first BI vendor around, their OLAP Services product was unique and significantly helped increase overall awareness of the possibilities offered by BI. Microsoft started gaining market share fairly quickly, as more as more companies started investing in BI solutions.
But as the years passed by, it became very apparent that while the type of multidimensional BI empowered by OLAP technology was a valuable asset to any organization, it seemed to be used mainly by large corporations. OLAP is just too complex and requires too much time and money to be implemented and maintained, thus eliminating it as a viable option for the majority of the market.
See: Microsoft (SSAS), IBM (Cognos)
The Visualization Front-End Craze
As more companies began investing in BI solutions, many vendors recognized the great opportunity in bringing BI to the mass market of companies with less money to spend than Fortune 500 firms. This is where visualization front-end vendors started popping up like mushrooms after the rain, each of them promising advanced business analytics to the end user, with minimal or no IT projects involved. Their appeal was based on radically reducing the infamous total cost of ownership (TCO) of typical BI solutions. These products, many of which are still available today, are full of useful and advanced visualization features.
However, after years of selling these products, it became very clear that they are incapable of providing a true alternative to OLAP-based solutions. Since they fail to provide similar centralized data integration and management capabilities, they found themselves competing mainly with Excel, and were being used only for analysis and reporting of limited data sets by individuals or small workgroups.
In order to work around these limitations (and increase revenues), these tools were introduced connectivity to OLAP sources as well as to the tabular (e.g., spreadsheet) data they supported until then. By doing that, these products basically negated the purpose for which they were initially designed – to provide an alternative to the expensive OLAP-based BI solutions.
See: Tableau Software, Tibco SpotFire, Panorama Software
The In-Memory Opportunity
The proliferation of cheap and widely available 64-bit PCs during the past few years has somewhat changed the rules of the game. More RAM could be installed in a PC, a boon for those visualization front-end vendors struggling to get more market share. More RAM on a PC means that more data can be quickly queried. If crunching a million rows of data on a machine with only 2GB of RAM was a drag, users could now add more gigabytes of RAM to their PCs and instantly solve the problem. But still, without providing centralized data integration and management, this was not a true alternative to OLAP-based solutions that are still prominent in massive organization-wide (or even inter-departmental) implementations.
Strangely enough, out of all the in-memory technology vendors out there, only one realized that using in-memory technology to empower individual users wasn't enough and that the way to gain more significant market share was to provide an end-to-end solution, from ETL to centralized data sharing to a front-end development environment. This vendor is QlikTech and it is no wonder that the company is flying high above the rest of the non-OLAP BI players. QlikTech used in-memory technology to cover a much wider range of BI solutions than any single front-end visualization tool could ever do.
By providing data integration and centralized data access capabilities, QlikTech was able to provide solutions that, for other vendors (in-memory or otherwise), required at least a lengthy data warehouse project if not a full-blown OLAP implementation. By utilizing in-memory technology in conjunction with 64-bit computing, QlikTech solutions work even on substantial amounts of data (significantly more than their traditional disk-based competitors could).
However, QlikTech has not been able to make a case for replacing OLAP yet. I believe this is not only because of the scalability issues and hardware requirements involved when large amounts of data and/or users are involved, but it’s also because they do not inherently support dimensional modeling like OLAP does. Apart from making life simpler for IT when maintaining multiple applications, OLAP’s implementation of a dimensional model also gives end users, via supporting front end tools, a broader range of flexibility in creating their own BI applications.
Microsoft, the newest entry into the in-memory BI game, also started marketing its in-memory PowerPivot solution as an alternative to OLAP, basically admitting it gives up on its Analysis Services as a viable solution for the wider mid-market.
See: QlikTech (QlikView), Microsoft (PowerPivot)
The SaaS/Cloud BI Hype
The SaaS/Cloud hype hasn’t skipped over the BI space, though running BI in the cloud does not dramatically change anything in respect to implementation time and/or complexity of implementation. In fact, cloud BI vendors use the same technologies that are widely used on-premises. There are several startup companies in this space, competing for niche markets. It’s still hard to tell what impact the cloud would have on the BI space as a whole as none of these companies has yet to prove there’s even a viable business for hosting BI in the cloud. One thing is certain, though: these companies cannot rely on in-memory technology to grow significantly. The costs of hardware and the amount of work required to support the number of customers they would need to thrive are prohibitive, to say the least. For more on the problem with cloud BI, see my earlier post, Would I Use Cloud Business Intelligence?
See: GoodData, YouCalc, Birst, PivotLink, Indicee
ElastiCube: Convergent Technologies for an Optimum Solution
ElastiCube technology was officially introduced to the market in late 2009, after more than five years of research and development conducted in complete secrecy. After being proved practical and effective in the real world (by being successfully implemented at over 100 companies, paying customers in numerous industries, from startups to multinational corporations), SiSense secured a $4 million investment to continue the development of the ElastiCube technology, and to expand awareness of the Prism Business Intelligence product which is based on the technology.
ElastiCube is the result of thoroughly analyzing the strengths and weaknesses of both OLAP and in-memory technologies, while taking into consideration the off-the-shelf hardware of today and tomorrow. The vision was to provide a true alternative to OLAP technology, without compromising on the speediness of the development cycle and query response times for which in-memory technologies are lauded. This would allow a single technology to be used in BI solutions of any scale, in any industry.
Here are the 10 main goals on which SiSense focused when designing the ElastiCube technology:
- A data warehouse must not be assumed to exist for effectively querying multiple sources.
- A star schema must not be assumed to exist for effective querying large amounts of data.
- The solution must provide unlimited scalability, both in terms of number of rows and number of fields, within a finite and reasonable amount of RAM.
- The solution must be able to operate using off-the-shelf hardware, even for extreme data/user scenarios.
- The solution must provide high-speed, out-of-the-box query performance, without requiring pre-calculations.
- There must be a separation between the application layer and the physical data layer via a virtual metadata layer.
- There must be support for a dimensional model and multidimensional analysis.
- The same application must be able to support a single user with a laptop to thousands of users via a central, server-based data repository.
- Without running an SQL database, an SQL layer must be available to conform to industry standards.
- The solution must offer the ability to incorporate additional/changed data (e.g., new rows, new fields) on the fly, without reprocessing the entire data model.
I can add that the feasibility of ElastiCube was greatly affected by the amazing CPU and disk technologies that now come with any run-of-the-mill personal computer.
ElastiCube is extremely powerful technology that enables speedy implementation of individual, workgroup and corporate-wide BI. As a solution that delivers the promise of OLAP-style BI without the cost, time and IT overhead of OLAP, it is no surprise that Prism is rapidly gaining popularity in the market. Businesses that use ElastiCube technology include household names such as, Target, Yahoo, Cisco, Samsung, Philips and Caterpillar. But a significant portion of business that use ElastiCube are significantly smaller, such as Wix and other startup companies - who otherwise could not afford BI at all.
See: SiSense (Prism)
"Plutora provides release and testing environment capabilities to the enterprise," explained Dalibor Siroky, Director and Co-founder of Plutora, in this SYS-CON.tv interview at @DevOpsSummit, held June 9-11, 2015, at the Javits Center in New York City.
Jan. 23, 2017 07:30 AM EST Reads: 3,695
"We provide DevOps solutions. We also partner with some key players in the DevOps space and we use the technology that we partner with to engineer custom solutions for different organizations," stated Himanshu Chhetri, CTO of Addteq, in this SYS-CON.tv interview at DevOps at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY.
Jan. 23, 2017 07:00 AM EST Reads: 4,791
@DevOpsSummit at Cloud taking place June 6-8, 2017, at Javits Center, New York City, is co-located with the 20th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The widespread success of cloud computing is driving the DevOps revolution in enterprise IT. Now as never before, development teams must communicate and collaborate in a dynamic, 24/7/365 environment. There is no time to wait for long developm...
Jan. 23, 2017 05:15 AM EST Reads: 3,592
True Story. Over the past few years, Fannie Mae transformed the way in which they delivered software. Deploys increased from 1,200/month to 15,000/month. At the same time, productivity increased by 28% while reducing costs by 30%. But, how did they do it? During the All Day DevOps conference, over 13,500 practitioners from around the world to learn from their peers in the industry. Barry Snyder, Senior Manager of DevOps at Fannie Mae, was one of 57 practitioners who shared his real world journe...
Jan. 23, 2017 03:45 AM EST Reads: 1,009
Adding public cloud resources to an existing application can be a daunting process. The tools that you currently use to manage the software and hardware outside the cloud aren’t always the best tools to efficiently grow into the cloud. All of the major configuration management tools have cloud orchestration plugins that can be leveraged, but there are also cloud-native tools that can dramatically improve the efficiency of managing your application lifecycle. In his session at 18th Cloud Expo, ...
Jan. 23, 2017 03:00 AM EST Reads: 6,173
We call it DevOps but much of the time there’s a lot more discussion about the needs and concerns of developers than there is about other groups. There’s a focus on improved and less isolated developer workflows. There are many discussions around collaboration, continuous integration and delivery, issue tracking, source code control, code review, IDEs, and xPaaS – and all the tools that enable those things. Changes in developer practices may come up – such as developers taking ownership of code ...
Jan. 23, 2017 01:45 AM EST Reads: 1,840
As 2016 approaches its end, the time to prepare for the year ahead is now! Following our own advice, we sat down with three XebiaLabs thought leaders–Andrew Phillips, Tim Buntel, and TJ Randall–and asked what they think the future has in store for the DevOps world. In 2017, we’ll see a new wave of “next gen platform” projects focused on container orchestration frameworks such as Kubernetes, and re-tooled PaaS platforms such as OpenShift or Cloud Foundry. Acceptance of the need for a cross-machi...
Jan. 23, 2017 01:45 AM EST Reads: 2,241
Software development is a moving target. You have to keep your eye on trends in the tech space that haven’t even happened yet just to stay current. Consider what’s happened with augmented reality (AR) in this year alone. If you said you were working on an AR app in 2015, you might have gotten a lot of blank stares or jokes about Google Glass. Then Pokémon GO happened. Like AR, the trends listed below have been building steam for some time, but they’ll be taking off in surprising new directions b...
Jan. 23, 2017 12:45 AM EST Reads: 2,396
Containers have changed the mind of IT in DevOps. They enable developers to work with dev, test, stage and production environments identically. Containers provide the right abstraction for microservices and many cloud platforms have integrated them into deployment pipelines. DevOps and Containers together help companies to achieve their business goals faster and more effectively. In his session at DevOps Summit, Ruslan Synytsky, CEO and Co-founder of Jelastic, reviewed the current landscape of D...
Jan. 23, 2017 12:15 AM EST Reads: 5,155
When building DevOps or continuous delivery practices you can learn a great deal from others. What choices did they make, what practices did they put in place, and how did they connect the dots? At Sonatype, we pulled together a set of 21 reference architectures for folks building continuous delivery and DevOps practices using Docker. Why? After 3,000 DevOps professionals attended our webinar on "Continuous Integration using Docker" discussing just one reference architecture example, we recogn...
Jan. 22, 2017 10:15 PM EST Reads: 1,449
An overall theme of Cloud computing and the specific practices within it is fundamentally one of automation. The core value of technology is to continually automate low level procedures to free up people to work on more value add activities, ultimately leading to the utopian goal of full Autonomic Computing. For example a great way to define your plan for DevOps tool chain adoption is through this lens. In this TechTarget article they outline a simple maturity model for planning this.
Jan. 22, 2017 08:45 PM EST Reads: 996
The proper isolation of resources is essential for multi-tenant environments. The traditional approach to isolate resources is, however, rather heavyweight. In his session at 18th Cloud Expo, Igor Drobiazko, co-founder of elastic.io, drew upon his own experience with operating a Docker container-based infrastructure on a large scale and present a lightweight solution for resource isolation using microservices. He also discussed the implementation of microservices in data and application integrat...
Jan. 22, 2017 07:15 PM EST Reads: 3,662
In his General Session at DevOps Summit, Asaf Yigal, Co-Founder & VP of Product at Logz.io, will explore the value of Kibana 4 for log analysis and will give a real live, hands-on tutorial on how to set up Kibana 4 and get the most out of Apache log files. He will examine three use cases: IT operations, business intelligence, and security and compliance. This is a hands-on session that will require participants to bring their own laptops, and we will provide the rest.
Jan. 22, 2017 06:30 PM EST Reads: 5,033
Here’s a novel, but controversial statement, “it’s time for the CEO, COO, CIO to start to take joint responsibility for application platform decisions.” For too many years now technical meritocracy has led the decision-making for the business with regard to platform selection. This includes, but is not limited to, servers, operating systems, virtualization, cloud and application platforms. In many of these cases the decision has not worked in favor of the business with regard to agility and cost...
Jan. 22, 2017 06:00 PM EST Reads: 743
All organizations that did not originate this moment have a pre-existing culture as well as legacy technology and processes that can be more or less amenable to DevOps implementation. That organizational culture is influenced by the personalities and management styles of Executive Management, the wider culture in which the organization is situated, and the personalities of key team members at all levels of the organization. This culture and entrenched interests usually throw a wrench in the work...
Jan. 22, 2017 06:00 PM EST Reads: 1,557
As the race for the presidency heats up, IT leaders would do well to recall the famous catchphrase from Bill Clinton’s successful 1992 campaign against George H. W. Bush: “It’s the economy, stupid.” That catchphrase is important, because IT economics are important. Especially when it comes to cloud. Application performance management (APM) for the cloud may turn out to be as much about those economics as it is about customer experience.
Jan. 22, 2017 03:15 PM EST Reads: 4,752
When you focus on a journey from up-close, you look at your own technical and cultural history and how you changed it for the benefit of the customer. This was our starting point: too many integration issues, 13 SWP days and very long cycles. It was evident that in this fast-paced industry we could no longer afford this reality. We needed something that would take us beyond reducing the development lifecycles, CI and Agile methodologies. We made a fundamental difference, even changed our culture...
Jan. 22, 2017 03:00 PM EST Reads: 1,214
SYS-CON Events announced today that Dataloop.IO, an innovator in cloud IT-monitoring whose products help organizations save time and money, has been named “Bronze Sponsor” of SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Dataloop.IO is an emerging software company on the cutting edge of major IT-infrastructure trends including cloud computing and microservices. The company, founded in the UK but now based in San Fran...
Jan. 22, 2017 02:30 PM EST Reads: 2,646
Internet of @ThingsExpo, taking place June 6-8, 2017 at the Javits Center in New York City, New York, is co-located with the 20th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. @ThingsExpo New York Call for Papers is now open.
Jan. 22, 2017 02:30 PM EST Reads: 3,768
The 20th International Cloud Expo has announced that its Call for Papers is open. Cloud Expo, to be held June 6-8, 2017, at the Javits Center in New York City, brings together Cloud Computing, Big Data, Internet of Things, DevOps, Containers, Microservices 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 ...
Jan. 22, 2017 02:00 PM EST Reads: 5,305