In financial organizations, as we are in the year 2015, business is almost always demanding analytics in real time.
As discussed in the previous chapter, Hadoop can process data in memory using Storm or Spark, but what a business really needs is the ability to combine the full historical dataset on disk with real-time in-memory data.
Lambda architecture addresses this requirement. The concept is very simple, yet powerful: Use both, the batch layer and the speed layer, using a shared serving layer, as shown next:
We already know which technologies are suited for batch layer and which ones for speed layer.