yahoo做的spark，storm 和 flink 性能对比测试
https://yahooeng.tumblr.com/post/135321837876/benchmarking-streaming-computation-engines-at
spark streaming， storm 浅度对比
结论：
storm低延迟，spark streaming吞吐量高
https://tsicilian.wordpress.com/2015/02/16/streaming-big-data-storm-spark-and-samza/
（很好）Spark Streaming vs Flink vs Storm vs Kafka Streams vs Samza : Choose Your Stream Processing Framework
1. 几个框架之间的对比
spark 和 flink比较重量级，flink比较前沿，streaming特性好，但batch特性还没有大公司采用，社区比spark细，但发展快，可以考虑。简单的业务场景可以使用其他框架，例如简单的IOT告警系统可以使用storm
2. Important Aspects of Stream Processing
Delivery Guarantees，Fault Tolerance ，State Management，Performance，Advanced Features : Event Time Processing, Watermarks, Windowing，Maturity
3. Two Types of Stream Processing
Native Streaming
Micro-batching
链接
https://www.linkedin.com/pulse/spark-streaming-vs-flink-storm-kafka-streams-samza-choose-prakash
作者的blog（可以参考）
https://why-not-learn-something.blogspot.com/2018/03/spark-streaming-vs-flink-vs-storm-vs.html
（未读）High-throughput, low-latency, and exactly-once stream processing with Apache Flink™
https://data-artisans.com/blog/high-throughput-low-latency-and-exactly-once-stream-processing-with-apache-flink
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