Your tooling selection really all depends on your particular use case.
For "Speed" layer, you can use Storm or Spark Streaming. IMHO the main selection criteria between the two will depend on whether you're interested in ultra low latency (Storm) or high throughput (Spark Streaming). There's other factors, but these are some of the main drivers.
For the "Serving" layer, your main choice is HBase. Depending on how you're going to query the "Serving" layer you may want to consider putting Phoenix on top of HBase. Since HBase is a NoSQL store, it has it's own API for making calls. Phoenix adds an abstraction layer on top of HBase and allows you to make queries in SQL format. Mind you, it's still in tech preview and may have some bugs here and there. Also, it's not meant for complex SQL queries.
For your ingest and simple event processing you can look into HDF/Nifi.
If you move beyond the HDP/HDF stack for the serving layer then your options increase to include other NoSQL stores as well as regular SQL DBs.
Below is a diagram of a sample Lambda architecture for a demo that receives sensor data from trucks and analysis them, along with driver behaviour, to determine the possibility of a driver committing a traffic violation/infraction. It will give you a better idea of what a lambda deployment may look like.
Your tooling selection really all depends on your particular use case.
For "Speed" layer, you can use Storm or Spark Streaming. IMHO the main selection criteria between the two will depend on whether you're interested in ultra low latency (Storm) or high throughput (Spark Streaming). There's other factors, but these are some of the main drivers.
For the "Serving" layer, your main choice is HBase. Depending on how you're going to query the "Serving" layer you may want to consider putting Phoenix on top of HBase. Since HBase is a NoSQL store, it has it's own API for making calls. Phoenix adds an abstraction layer on top of HBase and allows you to make queries in SQL format. Mind you, it's still in tech preview and may have some bugs here and there. Also, it's not meant for complex SQL queries.
For your ingest and simple event processing you can look into HDF/Nifi.
If you move beyond the HDP/HDF stack for the serving layer then your options increase to include other NoSQL stores as well as regular SQL DBs.
Below is a diagram of a sample Lambda architecture for a demo that receives sensor data from trucks and analysis them, along with driver behaviour, to determine the possibility of a driver committing a traffic violation/infraction. It will give you a better idea of what a lambda deployment may look like.
