With an exciting range of products democratising analytics capability, I caught up with Yaron Parasol, the Director of Products at Gigaspaces, to talk Big Data strategy.
Hi Yaron. Let’s start off by talking a little about what you guys do at Gigaspaces.
Gigaspaces has been around for quite a few years. I would say that we’re a leader in in-memory data platforms for scaling data and infrastructure applications. One of our central products is XAP, which is a combination of in-memory, data-driven, co-located processing capabilities which make it a scalable application platform. It notably allows extreme synchronous processing which means that you can trigger in transactions as well as asynchronous workflow using our event driven architecture.
How has your business changed over the last twelve months in terms of the products that you offer?
During the last few years we noticed that the Big Data market has started to grow quickly, particularly with the rise of Hadoop and NoSQL databases. We saw that more and more companies were getting involved in processing large volumes of data through batch processing over Hadoop or other such products either proprietary or open-source. We understood that there was something lacking there which we could very easily provide, which is the real-time streaming and processing of Big Data.
Big Data is defined by the three V’s, Volume, Velocity and Variability. We thought that given we are one of the best around Velocity and Variability what with our real-time expertise, this was definitely an area of importance for us. With the Volume aspect, we needed to learn how to interface with those Petabyte size sets of structured and unstructured data created by Hadoop or other such NoSQL databases. One of the notable innovations that we have recently introduced is a way to manage the entire set of end to end components. It can be managed across a single platform that can be run off the cloud.
In short we’re continuing to develop our products, meeting the needs of different enterprise customers, particularly fast companies that need to absorb large volumes of data at any given moment. We’re looking to continue to create real time insight from structured and unstructured real time data for further processing through our prospecting layer based on SAP.
What are the biggest challenges that you see you customers facing at the moment?
I think that for both enterprise customers and also for online services, they have to process huge amounts of data in order to remain competitive. Whether it is social media, from mobile phones, from crowd-sourcing applications or business measurement, it all needs to be processed in real-time in order for decisions to be relevant. Coping with these huge numbers of events without losing any pieces of data along the way is a huge challenge for the architecture. The demands of implementing a flexible architecture alongside facing up to the competitive marketplace that many of our clients are facing is a really potent combination.
The biggest challenge for our traditional clients within the financial vertical is the need to process more and more data in order to support growth. This is also true of eCommerce type businesses online, who are experiencing massive growth because of the rise of the mobile channel. They’re all trying to get a handle on real time.
Can SMEs take advantage of high end analytics technology?
Absolutely, in fact there are several enablers of this at the moment. The first is cloud technology, which allows SMEs to host elastic applications which can be used ‘on demand’ as well as reliable data centre access at reasonable cost, which is essential. So cloud is one pillar. The second are products such as ours which are becoming more and more mainstream. Before such products were available only the massive multi-nationals were able to afford in-house development and innovation in such technologies, whereas now it is becoming increasingly accessible to enterprises at all ends of the spectrum. It’s remarkable in fact how much customisation can be created without massive investment.
Do you see Big Data analytics becoming a norm going into 2013?
Before Big Data, companies reacted much slower to changes in the marketplace and to their customer. They were often left behind because competitors were able to identify trends earlier. Today, many more businesses realise that if you want to really increase profits they need to be more attentive. Big Data is an enabler of this. It’s all a matter of ROI. If the cost is reducing because of the flexibility of cloud and so on, we’re definitely going to more and more businesses getting stuck in to this space. The world is becoming more and more real time, which means that customers are expecting faster and faster service. Slow businesses are going to get left behind.