Ex-Google-Search engineer here, having also done some projects since leaving that involve data-mining publicly-available web documents. This proposal won't do very much. Indexing is the (relatively) easy part of building a search engine. CommonCrawl already indexes the top 3B+ pages on the web and makes it freely available on AWS. It costs about $50 to grep over it, $800 or so to run a moderately complex Hadoop job.…
Sure, it costs $50 to grep it, but how much does it cost to host an in-memory index with all the data? This is not a proposal to just share the crawl data, but the actual searchable index, presumably at arms length cost both internally & externally. The same ideas could be extended to the Knowledge Graph, etc. IMO the goal here should not be to kill Google, but to keep Google on their toes by removing barriers to com…
API access to either the unranked or ranked index in memory wouldn't do anything useful, BTW. To have a viable startup you need something a lot better than Google, which means that you need algorithms that do something fundamentally different from Google, which means you need to be able to touch memory yourself and not go through an API for every document you might need to examine. Remember, search touches (nearly) every indexed document on every query - if you throw in 200ms request latency for 4B documents your request will take roughly 25 years to complete.
Knowledge Graph is already public - it was an open dataset before it was bought by Google, and a snapshot of its state at the point Google closed it to further additions is still hosted by Google:
https://developers.google.com/freebase/
(It's only 22G gzipped, too - you can download that onto a personal laptop.)