Apache Storm – Introduction
- Apache Storm is a distributed real-time big data-processing system.
- Storm is designed to process vast amount of data in a fault-tolerant and horizontal scalable method.
- It is a streaming data framework that has the capability of highest ingestion rates.
- Though Storm is stateless, it manages distributed environment and cluster state via Apache Zookeeper.
- It is simple and you can execute all kinds of manipulations on real-time data in parallel.
- Apache Storm is continuing to be a leader in real-time data analytics.
Storm is easy to setup, operate and it guarantees that every message will be processed through the topology at least once.
- Basically Hadoop and Storm frameworks are used for analysing big data.
- Both of them complement each other and differ in some aspects.
- Apache Storm does all the operations except persistency, while Hadoop is good at everything but lags in real-time computation.
- The following table compares the attributes of Storm and Hadoop.
|Real-time stream processing||Batch processing|
|Master/Slave architecture with ZooKeeper based coordination. The master node is called as nimbus and slaves are supervisors.||Master-slave architecture with/without ZooKeeper based coordination. Master node is job tracker and slave node is task tracker.|
|A Storm streaming process can access tens of thousands messages per second on cluster.||Hadoop Distributed File System (HDFS) uses MapReduce framework to process vast amount of data that takes minutes or hours.|
|Storm topology runs until shutdown by the user or an unexpected unrecoverable failure.||MapReduce jobs are executed in a sequential order and completed eventually.|
|Both are distributed and fault-tolerant|
|If nimbus / supervisor dies, restarting makes it continue from where it stopped, hence nothing gets affected.||If the JobTracker dies, all the running jobs are lost.|
Apache Storm Benefits
Here is a list of the benefits that Apache Storm offers −
- Storm is open source, robust, and user friendly. It could be utilized in small companies as well as large corporations.
- Storm is fault tolerant, flexible, reliable, and supports any programming language.
- Allows real-time stream processing.
- Storm is unbelievably fast because it has enormous power of processing the data.
- Storm can keep up the performance even under increasing load by adding resources linearly. It is highly scalable.
- Storm performs data refresh and end-to-end delivery response in seconds or minutes depends upon the problem. It has very low latency.
- Storm has operational intelligence.
- Storm provides guaranteed data processing even if any of the connected nodes in the cluster die or messages are lost.