To better understand the differences among the relational database, NoSQL database, and Hadoop, let's compare them with ways of traveling. You will be surprised to find that they have many similarities. When people travel, they either take cars or airplanes, depending on the travel distance and cost. For example, when you travel to Vancouver from Toronto, an airplane is always the first choice in terms of the travel time versus cost. When you travel to Niagara Falls from Toronto, a car is always a good choice. When you travel to Montreal from Toronto, some people may prefer taking a car to an airplane. The distance and cost here are like the big data volume and investment. The traditional relational database is like the car, and the Hadoop big data tool is like the airplane. When you deal with a small amount of data (short distance), a relational database (like the car) is always the best choice, since it is fast and agile to deal with a small or moderate amount of data. When you deal with a big amount of data (long distance), Hadoop (like the airplane) is the best choice, since it is more linear-scalable, fast, and stable to deal with the big volume of data. You could drive from Toronto to Vancouver, but it takes too much time. You can also take an airplane from Toronto to Niagara Falls, but it would take more time on your way to the airport and cost more than traveling by car. In addition, you could take a ship or a train. This is like a NoSQL database, which offers characteristics and balance from both a relational database and Hadoop in terms of good performance and various data format support for moderate to large amounts of data.