title: Elasticsearch vs Cassandra vs Elasticsearch with Cassandra
body: <p>I am learning NoSQL and looking at different options for one of my client's requirements.  I have gone through various resources before putting up this question (a person with little knowledge in NoSQL)</p>
  
  <ul>
  <li>I need to store data at faster rate and read data. </li>
  <li>Fully fail-safe and easily scalable.</li>
  <li>Able to search through data for Analytics.</li>
  </ul>
  
  <p>I ended up with a short list of: <code>Cassandra and Elasticsearch</code></p>
  
  <p>What I do understand is Cassandra is a perfect NoSQL storage solution for me, as I can write data and read data using indexes.  Where it fails or it could fail is on Analytics. In the future, if I want to get data from <code>from_date to to_date</code>, or more ways to get data for analytics, if I don't design the Data model properly or keeping long term sight, which might be quite hard in ever changing world.</p>
  
  <p>While <code>Elastic Search</code> is best at indexing (backed by Lucene), and can search the data randomly by throwing some random text. But does it work the same for even if I want to retrieve data <code>from_date to to_date</code> (I expect it might be). But the real question is, is it a Search Engine, or perfect NoSQL data storage like Cassandra? If yes, why do we still need Cassandra?</p>
  
  <p>If both of these are in different world, please explain that! How do we combine them to get a more effective solution?</p>