Can you (or someone) comment on some of the important differences, in your mind? I'm quite new to NLP, so a knowledgable comparison of the two would be appreciated :)
Essentially spacy is better and faster at almost everything it supports but is not free for commercial use. I consider spacy a blessing for the Python and the NLP community in general. They have a great comparison with existing libraries at http://spacy.io/.
EDIT: From today on spacy is free for commercial use! (MIT license).
We're making good progress on multi-lingual support based on the Universal Dependencies scheme. We strongly value not rolling out features until they're ready for production use.
In most NLP libraries, you have to decode two things: what exists, and what you can actually build against. Often the first is well documented, but for the second you might be left with no comment at all, even if the model does not produce output usefully better than chance. You just have to try it out and see for yourself.
Multi-lingual support is not there yet. But when it is it'll be good.
Multi-lingual support is an important issue, and a key reasons I decided to relocate from Sydney and base the business in Berlin. My new co-founder, Henning Peters, is a native speaker of German.
It's better than textblob / nltk in many ways.