Difference between BSP model and synchronous round model in distributed computing
In the CONGEST model of distributed computing, the topology of the computer network is a graph $G$. In each round, each node can send a message to each of its neighbours in $G$. Typically, we assume that $G$ is unknown, we interpret the structure of $G$ as the input, and we are interested in solving graph problems related to the structure of $G$.

This is the key difference. In BSP there is no underlying graph topology that limits communication; in CONGEST there is a graph that determines who can talk directly with whom.



However, things get interesting if we set $G = K_n$ in the CONGEST model. That is, the network topology is a complete graph on $n$ nodes. This way we arrive at a model called the congested clique.

The congested clique is very closely related to the BSP model. The key difference is the following:


Congested clique: the bandwidth constraints are on the edges; for each pair of nodes $u$ and $v$, in each round $u$ can send at most $b$ bits to $v$.
BSP: the bandwidth constraints are on the nodes; for each node $u$, in each round $u$ can send at most $B$ bits in total to all other nodes, and receive at most $B$ bits in total from all other nodes.


Clearly, any congested clique algorithm is trivial to simulate in the BSP model if we have $B = nb$, with only a constant overhead. [I am ignoring some issues related to the local computation.]

Lenzen (2013) shows that the converse is also true: any BSP algorithm can be simulated in the congested clique model if we have $B = nb$, with only a constant overhead.

In summary, if we eliminate $G$ from the CONGEST model, we basically arrive at the BSP model. Hence the graph $G$ is the only difference between the models.