Top Apache Flume Alternatives

Big Data is a collection of large datasets. The data that we want to analyze is mostly generated in cloud servers, enterprise servers, application servers, social networking sites, and other data sources. It is recorded in the form of log files and then transported to a Hadoop environment for further analysis. Apache Flume is a reliable and distributed system that helps to efficiently aggregate and move massive quantities of these streaming data into HDFS or Hadoop Distributed File System. It is quite robust in its build and has multiple failovers and recovery functionalities for fault tolerance and tunable reliance. 

Data flow model for online analytic application

The JVM process is the Flume agent that allows the flow of events from the source to the destination. The source consumes events from a web server or similar external source and stores it into one or channels passively until a sink consumes it. After that, it moves into the HDFS or to the next agent. This propagation of events accounts for a flexible and robust design. You can schedule the accumulation of data or make it event-driven. Because Flume also has its own query processing engine, the transformation of each new data batch takes place without any hassle.    

Flume comes with multi-source support

To get started with Apache Flume, you need a Java 1.8, or later version, sufficient memory, and disk space and directory read/write permissions. It then lets you build multi-hop flows. Data can flow through more than one agent to reach the destination Hadoop with provisions for fan-in and fan-out flows. For failed hops, it has contextual routing and backup routes. The use is not limited to the aggregation of log data in a centralized data storage facility. Instead, it makes use of the customizability of data sources and pulls in data from network traffic, social media, email messages, and others.    

Reliable delivery of events

Flume offers various levels of reliable delivery of events. There is the best-effort delivery (no tolerance for node failures) and the end-to-end delivery (guaranteed delivery despite the occurrence of multiple failures). The events will be removed from the channel only when they reach the next agent or the final repository so that no data is lost in the journey. The file channel is durable and supported by the local file system. It also involves a memory channel for faster propagation. However, if the events are left behind in this channel after the agent process terminates, unfortunately, they are irrecoverable.