Streaming Computing product comparisons (Storm, Trident, Spark streaming, Flink)

product	model	API	warranty	fault tolerant mechanism	State Management	Delay	Throughput	Maturity
Strom	Native	Combined	At-least-once	Record ACKs	No	Very Low	Low	High
Trident	Mirco-batching	Combined	Exectly-once	Record ACKs	Operation-based state management	Low	Low	High
Spark Streaming	Mirco-batching	Declarative	Exectly-once	RDD Checkpoint	Ddstream-based state management	Low	Low	High
Flink	Native	Combined	Exectly-once	Checkpoint	Operation-based state management	Low	High	Low

1. Model Streaming ModelsNAITVE: Data into the immediate processing, Micro-batch: Data inflow, first divided into Micro-batch, and then processing; 2. API formModular: Operation more basic API operation, step by step fine control, each set up a combination of definitions assembling topology; declarative: provides high-order functions after encapsulation. The package can provide preliminary optimization, and can provide advanced operation such as window management and state management. 3. Guarantee MechanismAt-least-once, at least once, error cases need to be executed multiple times, exectly-once, one execution, ensure OK; 4. Fault-tolerant mechanismRecord ACKs, after each tuple is processed by ACK confirmation; Rdd Checkpoint, Checkpoint based on Rdd. Only need to recalculate specific rdd; Checkpoint:flink's Checkpoint, is a snapshot (to be added in detail) 5. State ManagementOperation-based state management: each operation has a state, data-based state management: Each data has a corresponding processing state; 6. Delay & Throughput

How to make a test plan. 7. Maturity Level

Product maturity, based on the Flink has been distributed in 2016.3 1.0 versions, how to define the maturity level. 8. PostScript

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There's a good translation document: Http://developer.51cto.com/art/201603/507444.htm