New technology brings continuous streaming analytics to any device
IBM Quarks, believed to be a breakthrough technology, now available to the open source community that embeds streaming analytics onto IoT devices. Analyzing data at the edge continuously, this technology can help companies generate insights more quickly and reduce network communication costs. IBM has submitted a proposal to Apache Software Foundation to request incubation of Quarks.
As IDC predicts that the worldwide installed base of IoT endpoints will grow at a rate of 21.4% through 2019 to 25.6 billion endpoints with IDC expecting approximately 30 billion connections in 2020. These devices will be enabled with digital sensing, computing and communications capabilities, giving passive objects a digital voice and the ability to create and deliver new data streams.
Developers and data scientists can use the open source code in Quarks to build new apps that can handle massive amounts of IoT data streaming from sensors, smart meters, mobile communications and other connected devices. Businesses across industries -from automotive and healthcare to telecommunications and manufacturing -can reduce communication costs and decrease time to insight with Quark’s ability to deliver real-time analytics, boost application intelligence, and improve cognitive systems.
“As businesses require more efficient analytics for the variety of connected devices they’re using, Quarks can provide tremendous amounts of potential as a streaming analytics solution for the IoT. Its ability to integrate with a rich ecosystem of data sources, allows users to draw greater insight from more data with less work,” said Nagui Halim, IBM Fellow and Director, IBM Streams. “By contributing Quarks to the open source community, innovation will move faster, and can enable businesses to move from raw data to insight-driven actions more quickly.”
Quarks was conceptualized for the open source community based on the high scalability and dynamic adaptability of IBM Streams. Many clients today are using IBM Streams as a cost-efficient way to visualize data, help expand the use of data analytics to a much broader base of users, and help build new products and services.
