So, in essence that is one of the functions of the Supergiant API. We just released a few weeks ago, so AWS was our first target, but.. we are working to add support for other top cloud and on-premise providers as fast as we can. I think we are striving for OpenStack, Digital Ocean, and GCE for our next targets. If you have other targets solutions that you think we should look at, let us know :-)
Use the ELK Stack - Elasticsearch, Logstash, Kibana. Logstash is for ETL and data normalization. Kibana is for building cool visualizations. Elasticsearch for storing, processing, analysis, scaling and search.
Jono, my company, qbox.io is a provider of hosted Elasticsearch with deployments on any data center in the AWS, Rackspace, and Softlayer public clouds. You could think of us as a MongoHQ for Elasticsearch.
Yes, it will be more expensive than the infrastructure by itself, but it will also come with fast and easy Elasticsearch deployment, scaling, and support from some of the best in the business. I love Linode and AWS, but they will not know how to help you with application-specific questions.
I think you might be attributing motives where none exist, vertex. We are a US-based company, of course subject to all the same laws. The EU datacenter was in development prior to this news breaking. The effort was solely in response to customers in the EU experiencing latency due to a transoceanic hop. The hop negates much of the benefit of using a full-text search server.
Of course, privacy expectations are set by the customer, who controls access policies.
Just to show this can work, we put together a demo called "Million Person Search". This is, as you may have guessed, a table search with a million records to demonstrate how fast ElasticSearch is when it is powered by SSD's. There is a link to Github to document it. http://qbox.io/demos