Displaying 1 to 12 from 12 results

cudf - cuDF - GPU DataFrame Library

  •    C++

NOTE: For the latest stable README.md ensure you are on the main branch. Built based on the Apache Arrow columnar memory format, cuDF is a GPU DataFrame library for loading, joining, aggregating, filtering, and otherwise manipulating data.

OmniSciDB - Open Source Analytical Database & SQL Engine

  •    C++

OmniSciDB is the foundation of the OmniSci platform. OmniSciDB is SQL-based, relational, columnar and specifically developed to harness the massive parallelism of modern CPU and GPU hardware. OmniSciDB can query up to billions of rows in milliseconds, and is capable of unprecedented ingestion speeds, making it the ideal SQL engine for the era of big, high-velocity data.

pygdf - GPU Data Frame

  •    Jupyter

PyGDF implements the Python interface to access and manipulate the GPU Dataframe of GPU Open Analytics Initialive (GOAI). We aim to provide a simple interface that similar to the Pandas dataframe and hide the details of GPU programming.

mapd-charting - Dimensional charting built to work natively with crossfilter rendered using d3.js

  •    Javascript

Dimensional charting built to work natively with crossfilter rendered using d3.js. MapD-Charting is a superfast charting library that works natively with crossfilter that is based off dc.js. It is designed to work with MapD-Connector and MapD-Crossfilter to create charts instantly with our MapD-Core SQL Database. Please see examples for further understanding to quickly create interactive charts.




mapd-charting - Dimensional charting built to work natively with crossfilter rendered using d3.js

  •    Javascript

Dimensional charting built to work natively with crossfilter rendered using d3.js. MapD-Charting is a superfast charting library that works natively with crossfilter that is based off dc.js. It is designed to work with MapD-Connector and MapD-Crossfilter to create charts instantly with our MapD-Core SQL Database. Please see examples for further understanding to quickly create interactive charts.

metis - Tools for massively parallel and multi-variate data exploration

  •    Javascript

Tools for massively parallel and multi-variate data exploration. Quickly build interactive visualizations powered by the speed of MapD Core.

jupyterlab-omnisci - OmniSci integrations for JupyterLab

  •    Jupyter

Connect to OmniSci, query their databases, and render the OmniSci-flavored Vega specification, all within JupyterLab. You can open an OmiSci SQL editor by going to File > New > OmniSci SQL Editor or clicking the icon on the launcher.


mapd-vega-mapboxgl-demo - example of using vega spec for mapd backend rendering with mapboxgl.js

  •    Javascript

standalone example of integrating mapd backend rendering and mapboxgl

metis - Tools for massively parallel and multi-variate data exploration

  •    Javascript

Tools for massively parallel and multi-variate data exploration. Quickly build interactive visualizations powered by the speed of MapD Core.

omnisci-tweetmap-2 - Play with and instantly visualize hundreds of millions of realtime tweets, from the global level all the way down to your neighborhood

  •    Javascript

Note that the above script will install several libraries as git submodules in ./lib. This requires that you have configured an SSH connection with Github, so that git clone may use ssh and not https.

omnisci-vega-mapboxgl-demo-philly-parking - Custom OmniSci app using Vega and MapboxGLJS

  •    Javascript

A barebones example of using the Vega spec for OmniSci backend rendering with MapBoxGL.JS. Parking violations data obtained from Open Data Philly. Note: You need a Mapbox API key in order to use this repo (set the value here), as well as OmniSci Enterprise Edition for its backend rendering capabilities.






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