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Building Server in Julia and Connecting to a Database

Introduction

With the growing popularity of the internet, building a web server has been an absolutely required skillset for any developer. However, there are popular frameworks in some languages available (like Node.js or Django) to build the backend. Still, Julia, being a relatively new language, also provides a framework for the same purpose. Julia is still under active development phase and has closer compiler performance to C than other languages.  Developers who have already implemented a machine learning or some data processing algorithm in Julia can now use the Julia Genie framework to expose APIs as well, which would help them use the same stack for the whole backend.

Installing Julia

If Julia is already installed in the system, typing $julia --version in the terminal should give version of Julia installed locally. Otherwise, official Julia documentation can be referred for installation. If installed properly, typing $julia in the terminal should start Julia in REPL mode.

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Introduction to Benchmarking in Julia

For the number of years I’ve been programming using Julia, I’ve never really been concerned with performance. Which is to say, I’ve appreciated that other people are interested in performance and have proven that Julia can be as fast as any other performance language out there. But I’ve never been one to pour over the Performance Tips section of the Julia manual trying to squeeze every last bit of performance.

But now that I’ve released OmniSci.jl, and as a company one of our major selling points is accelerated analytics, I figured it was time to stop assuming I wrote decent-ish code and pay attention to performance. This post highlights my experience as a beginner and hopefully will show how others can get started in learning to optimize their Julia code.

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Announcing OmniSci.jl: A Julia Client for OmniSci

Today, I’m pleased to announce a new way to work with the OmniSci platform: OmniSci.jl, a Julia client for OmniSci! This Apache Thrift-based client is the result of a passion project I started when I arrived at OmniSci in March 2018 to complement our other open-source libraries for accessing data: pymapd, mapd-connector, and JDBC.

Julia and OmniSci: Similar in Spirit and Outcomes

If you’re not familiar with the Julia programming language, the language is a dynamically-typed, just-in-time compiled language built on LLVM that can achieve or beat the performance of high-performance, compiled languages such as C/C++ and FORTRAN. With the performance of C++ and the convenience of writing Python, Julia quickly became my favorite programming language when I started using it around 2013.