Derivatives seem easy to understand abstractly as the rate of change of something, higher order derivatives are the rate of change of the rate of change of something, and so on.
I, however, have trouble understanding what an integral is in a general sense. It can be thought of as the sum of the infinitely small rectangles in an shape, but what is it, with respect to the initial function? I don't really understand why integration is the inverse operation of derivation. either.

Integration can be seen as a mean value : if you have a function $f : [0,1] \rightarrow \mathbb{R}$, its mean value is $\int_0^1 f(x) dx$. That idea can be generalized to integrals over complicated domains, or for different measures (if you know a bit about measure theory).
From a probability point of view, this would translate as : the expectancy of a random variable $X$ is the integral $\int_{\Omega} X(\omega) d\mu(\omega)$, where $\Omega$ is the set of all possible events and $\mu(\omega)$ is the probability of the event $\omega$. For example, if you take a random number $\omega$ between 0 and 1, the expectancy of sin($\omega$) is $\int_0^1 sin(\omega) d\omega$.
Another interpretation is with velocity : if you move along a line at a non constant speed $v(t)$, then the distance achieved between times $t_0$ and $t_1$ is $\int_{t_0}^{t_1} v(t) dt$. (the mean speed is $\frac{\int_{t_0}^{t_1} v(t) dt}{t_1 - t_0}$ ).
If you want the rough idea of the link between integration (or more precisely, primitives) and derivation : if you draw thin rectangles, delimited by $f(a+k h)$ and $f(a+ (k+1) h)$ and sum it (essentially the usual method), and call the result $F$, then $F(a+h) - F(a) = h f(a)$ so that $\frac{F(a+h)-F(a)}{h}=f(a)$. $F$ is roughly a primitive of $f$, and its "rough" derivation is $f$.