The difference here is that we produce a quantum annealer, which is useful for optimization problems instead of for database searches + factoring. It's already delivering some real-world value for early applications.
While gate model machines are interesting, D-Wave took the tack of implementing the model of QC most likely to lead to actual useful applications within our lifetimes. Gate-model QC does seem to be very useful, but until it reaches millions of physical qubits it's not going to be producing any results beyond pet laboratory projects, and it remains to be seen if that's even physically possible. In contrast, quantum annealing has been able to grow at a good rate both in terms of qubit count, degree of connectivity between qubits, and also in terms of reaching lower noise and better quality results.
We also have hybrid solvers that combine the state of the art in classical algorithms with QPU sampling to get the lowest energy state possible with a much larger graph than we can do in hardware.
I think it's a very interesting field to follow, there are huge investments being made and real progress is happening on a number of fronts. Our competitors are trying to bring live systems to market, too, but it's harder to see them being much more useful than simulators for the foreseeable future.