R vs Go: 30 Metrics Comparison

R vs Go

R

R is a Multi-paradigm programming language first appeared in 1993, designed by Ross Ihaka, Robert Gentleman. Main use cases: Data Science, Scientific Computing, Statistics.

Go

Go is a Procedural, Object-Oriented, Generic programming language first appeared in 2009, designed by Google. Main use cases: Systems Programming, Embedded, Performance-Critical Applications.

30 Metrics

Metric R Go
GitHub Stars 58302 59948
Stack Overflow Tags 729989 818506
TIOBE Rank 36 38
RedMonk Rank 20 31
PYPL Rank 24 32
Average Salary (USD) 122736 115006
Job Postings 38329 40063
Benchmarks Score 1.0 0.82
Learning Curve Hard Hard
Community Size Very Large Large
Documentation Quality 8 10
Ecosystem Maturity 10 9
Industry Adoption 8 8
Type System Complexity 9 10
Concurrency Support 8 6
Performance - Execution Speed 8 8
Performance - Memory Usage 9 9
Performance - Startup Time 8 6
Tooling Quality 8 8
Package Manager Quality 9 10
IDE Support 8 8
Debugging Experience 9 8
GitHub Stars Rank 20 19
Stack Overflow Tags Rank 25 17
Average Salary Rank 23 28
Job Postings Rank 22 16
Benchmarks Rank 4 28
Learning Curve Score 2 2
Community Size Score 9 8
AHP Score 7.66 7.5

AHP Score

  • R: 7.66 (#23)
  • Go: 7.5 (#25)
R               | ######## 7.66
Go              | ######## 7.5

When to choose R

Data Science, Scientific Computing, Statistics, Visualization. R is a Multi-paradigm programming language first appeared in 1993, designed by Ross Ihaka, Robert Gentleman. Main use cases: Data Science, Scientific Computing, Statistics.

When to choose Go

Systems Programming, Embedded, Performance-Critical Applications. Go is a Procedural, Object-Oriented, Generic programming language first appeared in 2009, designed by Google. Main use cases: Systems Programming, Embedded, Performance-Critical Applications.

Hello World Example

R:

print('Hello, World!')

Go:

package main
import "fmt"
func main(){ fmt.Println("Hello, World!") }

Other languages