There is just a memo about asymptotic notation of algorithms.
| big O | `T(x) = O(g(x))` | The growth rate of `f(x)` is asymptotically less than or equal to (<=) the growth rate of `g(x)`. |
| little o | `T(x) = o(g(x))` | The growth rate of `f(x)` is asymptotically less than (<) the growth rate of `g(x)`. |
| big omega | `T(x) = Ω(g(x))` | The growth rate of `f(x)` is asymptotically greater than or equal to (>=) the growth rate of `g(x)`. |
| small omega | `T(x) = ω(g(x))` | The growth rate of `f(x)` is asymptotically greater than (>) the growth rate of `g(x)`. |
| theta | `T(x) = Θ(g(x))` | The growth rate of `f(x)` is asymptotically equal to(=) the growth rate of `g(x)`. |
Here is a nice resource with Big-O cheat sheet.