I recently caught up with Mike Perez, Vice President of Services at Kinetica, to talk about GPU-accelerated databases and discuss how the Kinetica new Install Accelerator and Application Accelerator programs are are helping customers quickly integrate Kinetica into their environments. Mike leads the services and support teams at Kinetica, which enable successful customer deployments and provide the tools for customer long-term success with Kinetica. He has over 14 years of enterprise software experience as a software architect and consultant. Mike’s experience includes technical software positions at Hortonworks, Cloudera, Deloitte Consulting, and Sears Holdings. He also ran his own consulting firm, where he provided web application development consulting services. Mike earned a B.S.B.A. in Information Technology from the University of Denver.
What do the Kinetica Install Accelerator and Application Accelerator programs offer?
Our Install Accelerator and Application Accelerator programs are new software and services offerings that we developed to help organizations quickly integrate Kinetica into their environments. The Kinetica Install Accelerator is basically a pre-scoped consulting engagement and a one-year Kinetica license subscription for up to 1TB of memory. We’ll come into an organization and install, configure, and secure Kinetica in their environment, whether that’s on-site or in the cloud. We then provide detailed documentation and an operations runbook specifically for that company’s environment. Then, one of our consultants will come in and train their operations team on how to successfully operate their Kinetica instance.
The Kinetica Application Accelerator does just that—it accelerates the time it needed to design, build, and deploy their first application using Kinetica. In this case, one of our solution architects is on-site for a four-week engagement, and he/she will review their application requirements, design a solution, and help them implement their use case using Kinetica best practices. It also includes a one-year license subscriptions for up to 3TB of memory, as well as documentation and a runbook.
Why did Kinetica develop these Accelerator programs?
We developed these programs to help organizations quickly install and configure Kinetica within their enterprise environment and speed up the deployment of their GPU-accelerated solutions. We want to help customers get up to speed quickly and successfully with Kinetica, so they can get beyond the proof of concept phase and realize even more rapid ROI with these Accelerator programs and have the tools for long-term success.
What kinds of companies would want to take advantage of these Accelerator offerings?
Any company that wants to translate business requirements into best practices for integrating Kinetica into their environment, design solutions, and implement new use cases on Kinetica would greatly benefit from these Accelerator programs. It’s a great way to quickly move out of the test phase and into a full production use case.
What is a GPU-accelerated database?
Graphical processing units (GPUs) are becoming more and more accessible and usable within an enterprise environment. In fact, GPUs are basically changing the economics of distributed databases. Instead of having to use a huge amount of x86 processors, organizations can use fewer GPUs to drive real-time analytics applications. Databases that run on standard x86 hardware can take advantage of, at most, 32 processor cores. GPUs, on the other hand, bring as many as 4,000 additional cores to the process. With an accelerated GPU database, you can access data in mere milliseconds, versus 10 seconds with normal queries. GPUs are built to process millions of simple concurrent tasks, so a GPU-accelerated database is ideal for any company that needs to quickly break down workloads into repeatable processes.
With Kinetica, we’ve also added accelerated visualization capabilities. Our visualization tools can render large volumes of data on the fly, so Kinetica is particularly well suited for fast moving, location-based IoT data. Customers can plot billions of data points and see changes in real-time as the underlying data or queries change. For example, one large retailer uses Kinetica to better track their inventory in real time and improve customer engagement by correlating data from point of sales (POS) systems, social media, weather, and other data.
Why types of organizations would benefit from deploying a GPU-accelerated database?
Any organization that has use cases in real time would benefit from using a GPU-accelerated database. These types of use cases include sentiment analysis, anomaly and fraud prevention, resource allocation on the fly, terrorist tracking, energy generation optimization, inventory tracking and customer engagement improvements. That includes businesses across a wide range of industries: energy, telco, finance, retail, and healthcare, to name a few. In finance, for example, Kinetica helps companies get faster and more flexible insight into financial operations, customers, and markets. Retailers use Kinetica to track and analyze huge volumes of moving assets and inventory. Healthcare organizations take advantage of Kinetica’s brute-force computer power for patient monitoring/care, medical research, and billing/customer satisfaction improvement.
Since Kinetica applies GPUs to greatly accelerate parallel processing in a column-store engine, organizations can process over one billion simple operations in less than a second. That kind of speedup is more than 100-fold compared with leading in-memory and analytical databases. Basically, since Kinetica’s performance and efficiency greatly exceeds traditional in-memory databases, customers can realize much faster time to insights, while dramatically lowering their infrastructure costs.
Why are the primary benefits of a Kinetica GPU-accelerated database compared to CPU-based databases?
There are four main primary benefits of Kinetica’s GPU-based architecture: The first benefit is that we offer unprecedented performance—Kinetica can ingest streaming data while delivering analytic results and producing visualizations on that data within milliseconds. Second, because GPUs are embedded into the architecture, there are 4,000-plus cores per device, versus 8 to 32 cores per CPU-based device. Third, Kinetica can easily plug into existing data architectures, so the ops team doesn’t need to spend time tuning, indexing, or tweaking their system compared to traditional CPU-based solutions. It’s also easy to consume data, since we offer free-text search, a native visualization engine, and plug-ins with BI applications such as Tableau, Kibana, and Caravel.
Sign up for the free insideBIGDATA newsletter.