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Kinetica Now Available as a Service in AWS Marketplace

Kinetica, the database for time & space, is now easily accessible as-a-service in AWS Marketplace, a curated digital catalog that customers can use to find, buy, deploy and manage third-party software, data and services to build solutions and run their businesses on Amazon Web Services (AWS). The listing gives organizations real-time analysis and modern location intelligence on massive IoT data sets.

Many existing databases, even those with special object-relational extensions for spatiotemporal data, have struggled to keep up the scale, speed, and specialized analytics required for modern location intelligence workloads. They were never designed to handle the variety of fusion steps and geometry changes in an acceptable latency profile required to power downstream value-added location aware services. Kinetica applies an innovative compute paradigm, commonly referred to as vectorization, to radically reduce the complexity and increase the scale and performance of spatiotemporal workloads.

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Kinetica is available in AWS Marketplace and is fully managed by Kinetica. “Customers across government and commercial industries have been modernizing their location intelligence applications with Kinetica on AWS for years,” said Mona Chadha, Director of AWS Marketplace Category Management. “The availability of Kinetica as a fully managed service in AWS Marketplace allows those customers to purchase quickly via pay-as-you-go (PAYG) or Private Offers, automatically provision environments, and simply integrate their existing applications, enabling them to innovate faster and enhance their performance on AWS.”

Organizations across industries rely on Kinetica to analyze data from sensors and machines in real time. For instance, one of the largest global automakers uses Kinetica to deliver dynamic, real-time intelligence as part of their connected car program, and several of the largest global telco’s use Kinetica to optimize 5G network planning with coverage visualizations. At a top financial services firm, for instance, a 700-node Spark cluster running queries in hours took seconds on 16 nodes of Kinetica. At a top retailer, 100 nodes of Cassandra and Spark were consolidated into eight Kinetica nodes.

By harnessing built-in vectorization capabilities of the latest generation of chips from Nvidia and Intel in AWS, Kinetica now delivers fast querying of large volumes of streaming geospatial and time-series data. Consumption-based pricing lets users choose between CPU or GPU pricing.

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“Vectorization historically required exotic hardware and specialized–and scarce–skills, putting it out of reach to all but the largest and most well-funded organizations or government entities,” said Nima Negahban, Founder and Chief Executive Officer at Kinetica. “With Kinetica now available as-a-service in AWS Marketplace–this really levels the playing field for organizations looking to harness this next-generation technology to get the full value of streaming geospatial and time-series data.”

“Kinetica’s fully-vectorized database on AWS offers incredible performance by harnessing data-level parallelism using the built-in Advanced Vector Extensions (AVX-512) of 3rd Gen Intel Xeon Scalable processors,” says Jeremy Rader, GM of Enterprise Strategy & Solutions in the Datacenter and AI Group at Intel. “Across multiple industries, building intelligent, AI-powered applications with access to up-to-date time series and location data is becoming key to success,” said Scott McClellan, Senior Director of Data Science and MLOps at NVIDIA. “Kinetica has a long history of working with NVIDIA to optimize their real-time analytics database with accelerated computing, and the availability of Kinetica in AWS Marketplace greatly increases the accessibility of NVIDIA-powered processing for data scientists and data engineers.”

Deloitte estimates that IoT devices capable of sharing their location will represent 40% of all IoT data by 2025, making spatiotemporal data – where objects are and where they are moving – the fastest growing segment of big data. Prime examples are streams of IoT data from mobile devices, static or moving sensors, satellites, and video feeds from drones and closed-circuit TVs. Applications based on real-time spatial and time-series data are driving digital transformation across industries, including autonomous driving, monitoring the spread of disease, threat hunting in cybersecurity, fleet monitoring, climate change detection, smart energy management, retail proximity marketing, and many others.

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