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    <p>A SQL solution isn't necessarily what you want regardless of scale. There are situations where you can't easily predict the schema of your model, or worst still your data is schemaless. In those situations you want a data model which doesn't limit you but rather allows you the flexibilty you need to evolve your data while still maintaining core abilities such as fast indexes.</p> <p>Another reason is that SQL doesn't represent the natural way in which you want to look at your data, predominantly graph DBs such as Neo4J or GraphDB allow developers or users to approach a linked graph model in a more intuitive way.</p> <p>Of course there is a way to address all these issues in Oracle RDBMS, but it feels more like hacking the DB to fit your needs as opposed to using a DB that fits you. This sounds like a perk but it actually goes a long way into the ease of development and analysis of your application.</p> <p>Now if we are talking about scale, Oracle can probably beat column based DBs such as HBase or Hypertable, but it is important to note that Oracle RDBMS isn't just more expensive it's way way more expensive. In today's world even small time startups have Terabytes of data they need to analyze daily. Even small companies can use clusters of 100 machines in the cloud to store their data, in such a company Oracle isn't a viable option the annual licensing cost and the hiring of DBAs will prevent startups from using it.</p> <p>Finally the last reason why you would start off with NoSQL is speed, bringing up a MongoDB and starting development can be done in 5 minutes and sometimes you wanna handle problems as they come up and avoid premature optimization</p>
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