title: Database recommendation
body: <p>I have a collection of data that looks as follows:</p>
  
  <pre><code>id   name     c1    c2    c3    c4   ...  c50
  -----------------------------------------------
  1    string1  0.1   0.32  0.54 -1.2  ...  2.3
  2    string2  0.12  0.12 -0.34  2.45 ...  1.3
  ...
  (millions of records)
  </code></pre>
  
  <p>So I have an id column, a string column, then 50 floating point columns.</p>
  
  <p>There will be only one type of query run on this data that in a traditional SQL SELECT statement would look like this:</p>
  
  <p><code>SELECT name FROM table WHERE ((a1-c1)+(a2-c2)+(a3-c3)+...+(a50-c50)) &gt; 1;</code> where <code>a1,a2,a3,etc</code> are values that are generated before the query is sent (not housed in the data table).</p>
  
  <p>My question is this: <strong>Does anyone have any recommendations as to what type of database would handle this type of query the fastest.</strong>  I have used <code>SQL server</code> (which is majorly slow), so I am looking for other opinions.</p>
  
  <p>Would there be a way to optimize SQL server for this type of query? I have also been curious about column store databases such as <code>MonetDB</code>. Or perhaps a document store database such as <code>MongoDB</code>. Does anyone have any suggestions?</p>
  
  <p>Many thanks,
  Brett</p>