https://github.com/heavyai/heavyai.jl

Julia client for OmniSci GPU-accelerated SQL engine and analytics platform
https://github.com/heavyai/heavyai.jl

cuda data-science database gpu julia-language julia-package julialang sql

Last synced: 15 days ago
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Julia client for OmniSci GPU-accelerated SQL engine and analytics platform

• Host: GitHub
• URL: https://github.com/heavyai/heavyai.jl
• Owner: heavyai
• License: other
• Created: 2018-04-19T14:24:07.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2021-02-25T13:45:46.000Z (over 3 years ago)
• Last Synced: 2024-10-15T16:43:43.506Z (about 1 month ago)
• Topics: cuda, data-science, database, gpu, julia-language, julia-package, julialang, sql
• Language: Julia
• Homepage: https://omnisci.github.io/OmniSci.jl/latest/
• Size: 495 KB
• Stars: 21
• Watchers: 19
• Forks: 9
• Open Issues: 9
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

        
# OmniSci.jl

Linux: [![Build Status](https://travis-ci.org/omnisci/OmniSci.jl.svg?branch=master)](https://travis-ci.org/omnisci/OmniSci.jl) 


Codecov: [![codecov](https://codecov.io/gh/omnisci/OmniSci.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/omnisci/OmniSci.jl) 


[![](https://img.shields.io/badge/docs-stable-blue.svg)](https://omnisci.github.io/OmniSci.jl/stable/)

[![](https://img.shields.io/badge/docs-latest-blue.svg)](https://omnisci.github.io/OmniSci.jl/latest/)

JuliaCon 2019 OmniSci.jl announcement: https://www.youtube.com/watch?v=coPbmYuUah0 


Announcement blog post: [Announcing OmniSci.jl: A Julia Client for OmniSci](https://www.omnisci.com/blog/announcing-omnisci.jl-a-julia-client-for-omnisci)

## Support

This package is not officially supported by OmniSci, Inc. and is maintained only on a best-effort basis.

## Description

This package is an Apache Thrift-based client for OmniSci, with similar functionality to our Python package [pymapd](https://pymapd.readthedocs.io/en/latest/). Because of the rapid pace of [OmniSciDB](https://github.com/omnisci/omniscidb) development, this package will attempt to always run against the most recent version of OmniSci. In most cases, OmniSci.jl should be backwards compatible to the last few OmniSciDB releases, but if you run into an issue, the first step would be to run the OmniSci.jl test suite against the [newest stable CPU Docker image](https://hub.docker.com/r/omnisci/core-os-cpu) to validate the tests pass.