DifferentialEquations.jl is a metapackage for solving differential equations in the Julia programming language. It utilizes a novel confederated software architecture in order to encapsulate the over 70 packages of the JuliaDiffEq ecosystem into a single extensible API. Because of this, DifferentialEquations.jl consists of over 200 methods for solving ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), random differential equations (RDEs), continuous Markov chains (Gillespie SSA), mixed discrete and continuous evolution equations (hybrid equations, jump discussions), and (stochastic) partial differential equations ((S)PDEs). Wrappers over existing C++, Fortran, and MATLAB solvers are combined with a wide array of native Julia implementations to give rise to the largest collected set of algorithms, giving users a flexible way to solve difficult differential equations and methods researchers, as well as a test suite which covers the discipline. In addition, the native Julia solvers are consistently among the most efficient according to the extensive open testing and benchmarking suites hosted in the JuliaDiffEq organization (DiffEqBenchmarks.jl).

The features are documented in detail at https://diffeq.sciml.ai/stable/.