Sphinx lets you either batch index and search data stored in an SQL database, NoSQL storage, or just files quickly and easily — or index and search data on the fly, working with Sphinx pretty much as with a database server. Searching via SphinxAPI is as simple as 3 lines of code, and querying via SphinxQL is even simpler, with search queries expressed in good old SQL.
Performance and scalability Indexing performance:Sphinx indexes up to 10-15 MB of text per second per single CPU core, that is 60+ MB/sec per server (on a dedicated indexing machine).
Searching performance. Searching through 1,000,000-document, 1.2 GB text collection that we use for everyday development and testing runs at 500+ queries/sec on a 2-core desktop machine with 2 GB of RAM.
Biggest known Sphinx cluster indexes 25+ billion documents, resulting in over 9TB of data.
Busiest known one is Craigslist, serving 300+ million search queries/day.