After having written the thesis and thought about that stuff for another few weeks, my résumé would be:
- Use asynchronous I/O to maximize single-node speed (twisted should be a good choice for python). It might be strange in the beginning, but it usually makes up for it, especially with languages that aren't good at threading (ruby, python, ...).
- Redis is awesome! Fast, functional, beautiful :)
- Riak seems to be a great distributed datastore if you really have to scale over multiple nodes.
- Solr or Sphinx are just better optimized than most datastores when it comes to fulltext-search
- Take a day to look at graph databases (I'm still not 100% sure if I could have used one for my use cases)
Comments
After having written the thesis and thought about that stuff for another few weeks, my résumé would be:
- Use asynchronous I/O to maximize single-node speed (twisted should be a good choice for python). It might be strange in the beginning, but it usually makes up for it, especially with languages that aren't good at threading (ruby, python, ...).
- Redis is awesome! Fast, functional, beautiful :)
- Riak seems to be a great distributed datastore if you really have to scale over multiple nodes.
- Solr or Sphinx are just better optimized than most datastores when it comes to fulltext-search
- Take a day to look at graph databases (I'm still not 100% sure if I could have used one for my use cases)
Thanks for the tips! I really appreciate it. I'll check these out. All getting very exciting for my Christmas project!