what is better: up- or downsampling?
In short: 


Upsampling: does/should not loose information  (if done wisely), then safer,
Downsampling: may loose information (if done unwisely), yet more computationally  efficient.


So if you compare data at different rates, and in an evaluation phase when one tries to define how the comparison should be done (which features are compared, with what metric, with which externals, like precision, efficiently, robustness, etc), a very basic first approach would be to upsample both signals by an integer factor to reconcile their sampling. Here, this is quite OK, 6000 Hz could work for both.

The reasons could be, for DSP practice:


with integer upsampling, you are not obliged to use tricky filtering techniques, and simple linear interpolation is easy. Remember though that upsampling adds some information.
with signals are the same scale, you can extract features and compare them: noise, variability, slopes, derivatives, etc. You can apply the correct scale/offset correction (they don't have the same amplitude), use linear or non-linear transformations (Fourier, etc.) to check whether similarities features exist in different domains 
at this stage, you should be able to quality and quantify the features/metrics needed to build your algorithm. And you can estimate what you can loose from both data. For instance, you can create your algorithm, and see how it is robust to signal downsampling, and how far you can go. Here, your algorithm begin to be more efficient.


Once you have spent some time on that, you are more ready to start from scratch again, and decide whether you should downsample or not, with which method, etc. to reach both safety and efficienty.

To provide alternatives, if you decide to compare data on the Fourier domain, you can easily cast two signals with different length and sampling rate to the same number of Fourier coefficients, helping a comparison in the frequency domain.