US-based Kinetica to focus on Asia Pacific markets

  • Aims to help clients to understand the benefits of using a GPU
  • Particularly sees Indonesia as a booming market


US-based Kinetica to focus on Asia Pacific markets


SAN FRANSISCO-based company Kinetica that develops a distributed, in-memory database management system using graphics processing units (GPU), aims to focus on key Asia Pacific markets, namely, Indonesia, Singapore, South Korea, Japan, and Australia.

Kinetica director of solution engineering Asia Pacific Ghulam Imaduddin tells Digital News Asia about the company’s journey which began nine years ago.

In 2009, the United States Army Intelligence and Security Command (Inscom) were looking for a solution to produce instant results and visualise insights across massive streaming datasets so as to track national security threats in real-time.

Kinetica’s co-founders, Amit Vij and Nima Negahban, built from the ground-up a new database, centred around massive parallelisation utilising GPU, to explore and visualise data in space and time.

After the United States Postal Service’s deployment of Kinetica in 2014, they made their official entry into the commercial market in 2016 to help other businesses simultaneously ingest, explore, analyse and visualise data within milliseconds. This in turn helps companies makes critical, intelligent business decisions and gives them a competitive edge over their counterparts.

On March 3, 2016, the name of the company was changed to ‘GPUdb’ to match the name of the software, and a US$7 million investment was announced which included business strategist, Raymond J Lane.

In September 2016, it announced another US$6 million investment, and an office in San Francisco, while keeping its office in Arlington, Virginia. After adding marketing and service people, the name of both the company and product was changed to Kinetica.

“Since our entry into the commercial market, our business model has remained largely similar. In addition to taking a direct sales approach, we have also established partnerships with notable organisations such as launching an AI centre in Indonesia with Binus University and Networld in Japan, and are ramping up our presence among the channel enterprises,” says Ghulam.

He adds that Kinetica has grown significantly since it entered the commercial market in 2016. A year later in 2017, it closed a US$50 million Series A funding co-led by Canvas Ventures and Meritech Capital Partners with participation from Citi Ventures and existing investor Ray Lane of GreatPoint Ventures. In July 2017, it expanded to the Asia Pacific as part of its next phase of growth.

“A key growth driver for Kinetica would be the burgeoning data analytics market in the region, as well as across the globe. According to IDC’s Worldwide Semi-Annual Big Data and Analytics Spending Guide, Asia Pacific is expected to experience the fastest growth at a compound annual growth rate (CAGR) of 14.4% by 2022 in big data and business analytics spending.

“Additionally, as businesses move into the ‘Extreme Data Economy’, it is vital for them to look beyond just collecting data and instead, look for alternative solutions such as Kinetica’s instant insight engine to help them analyse the data as well as derive and act on intelligent business insights in real time.”

Targeting various industries

Kinetica targets sectors such as healthcare, energy, telecommunications, retail, logistics and financial services. The expansion of mobile, social, and cloud technologies has led to the big data phenomenon and the using of data to make better business decisions across industries.

According to We Are Social, the shares of website traffic were mostly from smartphones (69%), laptops and deskstop (28%), and tablet devices (2%) in 2017.

“Coupled with the growth in volume, velocity and variety of data streams, this proliferation of mobile, cloud, and IoT devices are now leading us to a new era: ‘the Extreme Data Economy’.”

Ghulam says this presents a completely new set of challenges around extreme data that powers businesses.

“To manage extreme data, companies need to address massive sets of complex data at unparalleled speed, with streaming data analysis, visual foresight, streamlined machine learning, all orchestrated around an innovation-focused ecosystem.”

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