Special thanks to all who participated in the survey!
1,844 Julia users and developers completed the survey from over 90 countries and fluent in more than 60 languages.
Key findings and methodology are below.
Most Popular Features / Biggest Problems
The most popular technical features of Julia are:
Ease of use
Solves the two language problem
The most popular non-technical features of Julia are:
Julia community of developers is talented and active
Easy to create packages
The biggest technical problems with Julia are:
Packages aren’t as mature or well-maintained as required
It takes too long to generate the first plot
The biggest non-technical problems with Julia are:
Colleagues, company or collaborators use other languages
Not enough Julia users in my field/industry
Reasons for Trying Julia
Julia users and developers say they first tried Julia because:
Julia seems like the language of the future
Faster for the work I am doing
I like learning new languages
I heard about Julia from friends or colleagues and wanted to try it out
Preferable syntax to other languages
Most users and developers use Julia for research (73%) or individual work (54%). 15% use Julia for development as part of a team and 10% use Julia in production for business critical task.
45% of Julia users and developers use Julia for at least half of their work.
The most popular Julia packages are:
Most Julia users and developers say the package environment is ‘somewhat’ robust.
Editors / IDEs
The most popular editors or IDEs are:
Julia in the Cloud
The most popular cloud solutions are:
Julia Community: 76% say the Julia community is very (47%) or somewhat (29%) helpful and collaborative. Only 2% say the community is not very helpful and collaborative.
JuliaCon: 12% have attended JuliaCon, 59% plan to or would like to attend and 23% are unlikely to attend JuliaCon in the future.
Julia Download and Installation: Most Julia users and developers (70%) downloaded binaries from JuliaLang.org. 17% compile Julia from source.
Accelerators: Most of those who use Julia with hardware accelerators use Nvidia GPUs.
60% of survey participants are academics while 43% are professionals (some are both)
Among academics, most are graduate or postgraduate students or researchers (56%) while 34% are instructors and 11% are undergraduates
Among professionals, most are engineers or developers (61%), 45% are researchers, 20% are analysts and 11% are managers
The most popular fields include:
Data science, statistics
Signal and image processing
Age: Most respondents are age 25-45, but a substantial number are age 50+
Country of origin and language: Despite the fact that the survey was conducted and publicized only in English, respondents come from more than 90 countries, including the US (22%) and Germany (9%) and are fluent in more than 60 languages
Ethnicity: 66% of respondents identify themselves as white, 13% as Asian, 7% Hispanic, 2% Middle Eastern, 1% black and 13% declined to answer
Gender: 85% of respondents identify themselves as men, 3% as women and 12% declined to answer
Sexual orientation: 4% of respondents identify themselves as LGBTQ, 79% do not and 17% declined to answer
Underrepresented in science or computing: Among the 81% who did not decline to answer, 20% identify as underrepresented in science or computing because of one or more of the following: race, ethnicity, national origin, religion, income, socioeconomic status, education level, parents’ education level, age, gender, sexual identity or disability
The survey was conducted June 12-26, 2019. 1,844 Julia users and developers participated, with a margin of error of +/- 2.3 percentage points. We recruited participants online using Slack, Discourse, Twitter, email, JuliaLang.org and JuliaComputing.com. The survey was administered in English, but more than half of respondents come from non-English speaking countries. Respondents come from more than 90 countries and are fluent in more than 60 different languages.