title: Is there any other way to find the similarity metric between the records with low overhead and high accuracy (other than Jaro-Winkler Algorithm)?
body: <p>I am trying to achieve similarity metric between strings with Jaro Winkler Algorithm in python, I am using anaconda environment and deployed it on Alibaba Cloud ECS Instance.</p>
  
  <p>The sample code I am using to find similarity:</p>
  
  <pre><code>from pyjarowinkler import distance
  print ("Average Score ----&gt;", distance.get_jaro_distance("hello", "haloa"))
  
  Average Score ----&gt;0.76
  </code></pre>
  
  <p>When I process 600k records it takes more than 20 mins. It is very slow to process large number of records. Is there any other way to find the similarity metric between the records with low overhead and high accuracy?</p>