  In this paper, we prove convergence rates for time discretisation schemes for
semi-linear stochastic evolution equations with additive or multiplicative
Gaussian noise, where the leading operator $A$ is the generator of a strongly
continuous semigroup $S$ on a Hilbert space $X$, and the focus is on
non-parabolic problems. The main results are optimal bounds for the uniform
strong error $$\mathrm{E}_{k}^{\infty} := \Big(\mathbb{E} \sup_{j\in \{0,
\ldots, N_k\}} \|U(t_j) - U^j\|^p\Big)^{1/p},$$ where $p \in [2,\infty)$, $U$
is the mild solution, $U^j$ is obtained from a time discretisation scheme, $k$
is the step size, and $N_k = T/k$. The usual schemes such as the exponential
Euler, the implicit Euler, and the Crank-Nicolson method, etc. are included as
special cases. Under conditions on the nonlinearity and the noise, we show
  - $\mathrm{E}_{k}^{\infty}\lesssim k \sqrt{\log(T/k)}$ (linear equation,
additive noise, general $S$);
  - $\mathrm{E}_{k}^{\infty}\lesssim \sqrt{k} \sqrt{\log(T/k)}$ (nonlinear
equation, multiplicative noise, contractive $S$);
  - $\mathrm{E}_{k}^{\infty}\lesssim k \sqrt{\log(T/k)}$ (nonlinear wave
equation, multiplicative noise)
  for a large class of time discretisation schemes. The logarithmic factor can
be removed if the exponential Euler method is used with a (quasi)-contractive
$S$. The obtained bounds coincide with the optimal bounds for SDEs. Most of the
existing literature is concerned with bounds for the simpler pointwise strong
error $$\mathrm{E}_k:=\bigg(\sup_{j\in \{0,\ldots,N_k\}}\mathbb{E} \|U(t_j) -
U^{j}\|^p\bigg)^{1/p}.$$ Applications to Maxwell equations, Schr\"odinger
equations, and wave equations are included. For these equations, our results
improve and reprove several existing results with a unified method and provide
the first results known for the implicit Euler and the Crank-Nicolson method.
