News room

The Rise in Spatial and Temporal Data Analysis

Vectorized databases are a type of distributed analytic database that uses vectorized query execution to boost performance.
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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,...
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Independent TPC-DS Benchmarks Analysis Of Kinetica And Altinity ClickHouse

The Kinetica database executed 98 of 99 queries in our six sequential (SQL 1 through 99) testing runs and demonstrated consistent performance values with very low deviation.
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The Rise of Real-time Location Intelligence

The fastest-growing kind of data this decade is real-time geospatial data. Specifically, we are talking about any data with an x and y coordinate that changes over time.
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Daily Scoop Podcast: Analyzing the data deluge

11:20 The federal IT dashboard is getting a makeover. One reason is the availability of more data about federal IT and getting that data faster than ever.
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Bank Replaces Hundreds of Spark Streaming Nodes with Kinetica

We took out 700 nodes of Spark and Redis, They were spending tons and tons of money on hardware and hundreds of thousands, millions of lines of Spark-Flink type code. We were able to reduce that to several thousand lines of SQL.
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Parallel Processing 2.0: Round Two, Ready Fight!

Vectorized CPUs have been gestating for decades. Now they are emerging as the innovator’s choice as they use parallel CPU instructions when working on a single user’s workload.
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Kinetica as a service is now available on Azure

Kinetica's fully-vectorized database on Microsoft Azure Marketplace significantly outperforms traditional cloud databases for big data analytics
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Taking Big Data Analytics to the Next Level with Native Vectorized Databases

Kinetica leverages the Intel® Advanced Vector Extensions 512 (Intel® AVX-512) to vastly accelerate big data analytics and achieve greater performance on fewer nodes
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Kinetica Fuses Streaming and Contextual Analysis At Scale

Kinetica, the database for time and space, today announced native integration with Kafka and an API Key integration with Confluent, the platform for data in...
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Curtiss-Wright Adds Kinetica Software Support to the PacStar® 453 GPU Module for Intelligent Sensor Data Analytics

When (Kinetica) is hosted on our rugged size, weight and power (SWaP) optimized PacStar 453 module, the combination provides a deployable solution for high performance cloud-based data analytics in the field.
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How Vectorization Is Helping Identify UFOs, UAPs, And Whether Aliens Are Responsible

Vectorization, or data-level parallelism, accelerates analytics exponentially by performing the same operation on different sets of data at once, for maximum performance and efficiency
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In-Memory Database Architecture: An Overview

Wherever the data lives is where the rest of the solution stack will move toward because data is expensive and the need to be able to have fast access and do mutations of that data is what drives all computing
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The Game-Changing Technologies Powering the Data-Driven Enterprise in 2021 and Beyond

Vectorized databases offer orders of magnitude performance improvements on common big data analytic workloads like aggregations, predicate joins, equi­joins, derived columns, window func­tions, graph solvers, and certain GIS func­tions
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How Data Science Helped Combat the Coronavirus Outbreak

Kinetica and Disaster Tech deployed a dynamic AI-powered analytical platform to assist the U.S. crisis responders to track coronavirus-related data on the fly
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HPC in the cloud is changing the game for startups

Kinetica is tapping Oracle Cloud HPC capacity to analyze huge datasets
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Drones for Trash Clean Up in Waterways Could Save the Oceans

Using an oil-detecting algorithm developed by Danish Technical University and cloud-based image-sensing software developed by streaming data analytics company Kinetica, the Mavic is able to detect even small amounts of oil or gasoline waste on the water’s surface
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Drones for the Environment: Battling Trash in San Francisco Estuaries

We are enabling these users to hook into these streaming feeds directly, stream them directly to a target table, and the second they hit that table form this type of analysis, a seamless end-to-end machine-learning work flow,
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