title: How to efficiently store document indexes
body: <p>I am working on semantic search system, that stores huge amount of data. The data actually are documents and their indexes. The main problems are how to index document using ontologies and how to store them. </p>
  
  <p>My question is about the second problem. At first, I implemented storing in RDBMS. It works veeery slowly. I consider to use some NoSQL database for this purpose, but have some doubts. </p>
  
  <p>Please note, that simple text search using Lucene is not what i need in the current field.</p>
  
  <p>Let me simplify the store structure. Note, that only inverted indexes are stored. In RDBMS we have tables:<br>
   1) Word - words from some dictionary<br>
   2) Document - document with metadata and it's content<br>
   3) Hit - word's hits in document (all hits separated by '|')</p>
  
  <p>To get result system analyses words in request and calculate doc relevance basing on word's hit info. I have omitted some moments about semantic analyze, it's not important for now.</p>
  
  <p>What do you think about this structure of the word storing?</p>
  
  <p>{<br>
      "word": "some_word",<br>
      ...<br>
      "some other metadata from the dictionary"<br>
      ...<br>
      "hits": [<br>
           "doc1" : [ "hit_info1", "hit_info2"...]<br>
           "doc2" : [ "hit_info1", "hit_info2"...]<br>
      ]<br>
  }  </p>
  
  <p>Thanks in advance!</p>