It is possible to use Spark instead of Hadoop, and it’s being done more and more often as developers begin to recognize the advantages of Spark. You can use Spark on Hadoop, you can use it without Hadoop, or you can combine the two.
If you already have Hadoop, there’s no reason to build Spark around it. And if you’re starting from scratch and are after the speed and real-time data analysis Spark provides, there’s no reason to build Hadoop first.
However, the answer really depends on what you’re trying to accomplish running big data with Spark. While Hadoop is designed to handle batch processing efficiently, Spark is designed to efficiently handle real-time data. So if you’re goal is to analyze real-time events, Spark Streaming might be the best option. When you need to do complicated resource management that you get from Hadoop’s resource managers, using Spark on Hadoop would be the best option.