Kinetica Blog
Analyzing Meetup RSVPs with Kinetica Part 2:
In the first part of this series we talked about new emerging types of data, how traditional databases might not be the best tool to process it, and what Kinetica can do to make the lives of developers and analysts easier when dealing with streaming and geospatial data problems....
The Kinetica Active Analytics Platform – What’s New
Earlier today we announced a new version of the Kinetica Active Analytics Platform – our next generation platform for building smart analytical applications at scale....
Keeping Up with the Kineticans: Irina Farooq
Welcome to “Keeping up with the Kineticans”, a casual interview series where we talk with some of our awesome teammates about life at Kinetica, their careers, and more....
Keeping Up with the Kineticans: Dipti Joshi
Welcome to “Keeping up with the Kineticans”, a casual interview series where we talk with some of our awesome teammates about life at Kinetica, their careers, and more....
Keeping Up with the Kineticans: Solongo Erdenekhuyag
Welcome to “Keeping up with the Kineticans”, a casual interview series where we talk with some of our awesome teammates about life at Kinetica, their careers, and more....
Good As Gold: Kinetica Kafka Connector Earns Top Certification from Confluent
We’re excited to announce that our Kinetica Kafka Connector has achieved Gold Certified status from Confluent!...
Analyzing Meetup RSVPs with Kinetica – Part One
Introduction
Geospatial data is everywhere. Mapping directions, tracking a package, and reading a weather report are all examples of how we use geospatial data in our daily lives....
Converging Data Science and Data Engineering with Our Open Source Integration for RAPIDS
Recently, NVIDIA announced RAPIDS, an open source data science library that enables data scientists to accelerate model training and development by harnessing the power of the GPU....
Working with RAPIDS Using Kinetica’s pyGDF Open Source API
With the rise of GPU computing, streamlining the processing of data on GPUs has become critical to increase the speed and efficiency of machine learning....
Kinetica Sparse Data Tutorial
Introduction
This tutorial describes the application of Singular Value Decomposition or SVD to the analysis of sparse data for the purposes of producing recommendations, clustering, and visualization on the Kinetica platform....