A wide variety of traffic models are presently used to study the performance of telecommunications networks. These are shown to be limiting cases of N-Burst/G/1 queues. The analytic N-Burst model describes traffic as a superposition of N packet streams of ON/OFF type, i.e., during its ON-time each source generates packets at rate lambda_p, and is quiet during its OFF time. When using Power-Tail Distributions for the duration of the ON periods, self-similar properties, which are critical for understanding tele-traffic, are observed. For very low intra-burst packet rates, the N-Burst/G/1 model reduces to an M/G/1 queue. For lambda_p -- infty all packets in a burst arrive simultaneously and the model becomes a Bulk arrival, or M^(X)/G/1, queue. In the same limit, the packet-based model can be compared to a model on the burst level, an M/G/1 queue where the individual customers represent complete bursts rather than individual packets. Thus the mean system time describes the mean delay for the last packet in a burst rather than the average over all packets. The continuous flow model is also shown to be a limiting case of the N-Burst model by letting the number of packets in a burst, n_p, and the router's packet service rate, nu, go to infinity while holding their ratio constant. Numerical results are presented comparing the steady-state results for Mean Packet Delay (mPD) and for Buffer Overflow Probabilities (BOP) of the different analytic models. They collectively show the critical importance of the Burstiness Parameter (the fraction of time that a source is OFF). The N-Burst/M/1 model with self-similar properties shows drastically changing steady-state performance for specific values of the Burstiness Parameter. The limiting models are incapable of describing the detailed structure of the performance in this transition region.