This topic is about Apache Flink – Flink vs Spark vs Hadoop.
Here is a comprehensive table, which shows the comparison between three most popular big data frameworks: Apache Flink, Apache Spark and Apache Hadoop.
| Apache Hadoop | Apache Spark | Apache Flink | |
|---|---|---|---|
| Year of Origin | 2005 | 2009 | 2009 |
| Place of Origin | MapReduce (Google) Hadoop (Yahoo) | University of California, Berkeley | Technical University of Berlin |
| Data Processing Engine | Batch | Batch | Stream |
| Processing Speed | Slower than Spark and Flink | 100x Faster than Hadoop | Faster than spark |
| Programming Languages | Java, C, C++, Ruby, Groovy, Perl, Python | Java, Scala, python and R | Java and Scala |
| Programming Model | MapReduce | Resilient distributed Datasets (RDD) | Cyclic dataflows |
| Data Transfer | Batch | Batch | Pipelined and Batch |
| Memory Management | Disk Based | JVM Managed | Active Managed |
| Latency | Low | Medium | Low |
| Throughput | Medium | High | High |
| Optimization | Manual | Manual | Automatic |
| API | Low-level | High-level | High-level |
| Streaming Support | NA | Spark Streaming | Flink Streaming |
| SQL Support | Hive, Impala | SparkSQL | Table API and SQL |
| Graph Support | NA | GraphX | Gelly |
| Machine Learning Support | NA | SparkML | FlinkML |
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Thanks for the post. Awesome.