Apache Flume is used for aggregating and analyzing log data in near-real-time across the organization for compliance purposes with a goal to generate monthly compliance reports based on log data.

Pros and Cons

Apache Flume being a log-centric system, it is able to parse and aggregate log data very well.
It is easy to customize it for different source (producers) for log data ingestion as well as for sinks (consumers).

It is very specific for log data ingestion so it is pretty hard to use for anything else besides log data
Data replication is not built in and needs to be added on top of Apache Flume (not a hard job to do though)

Apache Flume is well suited when the use case is log data ingestion and aggregate only, for example for compliance of configuration management. It is not well suited where you need a general-purpose real-time data ingestion pipeline that can receive log data and other forms of data streams (eg IoT, messages).

Support Rating

5

Apache Flume is open-source so support is limited. Never the less, it has great documentation and best practices documents from their end-users so it is not hard to use, setup and configure.

November 03, 2017

Apache Flume, the way your information flows

Juan Francisco Tavira

Global Technology Centre - Middleware

Produban (Financial Services, 10,001+ employees)

Score 7 out of 10

Vetted Review

Verified User

Use Cases and Deployment Scope

Apache Flume is a key software piece in BigData environments, we have used it along with CDC (Change Data Capture) to ingest near real time database changes into Kafka so the data is available for realtime analysis, machine learning, dynamic dashboards and so on.
We have successfully integrated also Apache Flume in log acquisition solutions (mainly PaaS and Docker) where application log is difficult access.

Pros and Cons

Multiple sources of data (sources) and destinations (sinks) that allows you to move data form and to any relevant data storage
It is very easy to setup and run
Very open to personalization, you can create filters, enrichment, new sources and destinations

Apache Flume develops new functionality at a slower pace than other OpenSource projects, it is well behing Kafka and has some compatibiliy issues with latest releases
It lack HA or FT, it relies on third party management software like Hortonworks or Cloudera

Likelihood to Recommend

Apache Flume is well suited in small batch and near real time processing projects, taking data from one point to another with local processing (I mean not external enrichment). Filtering, transforming and multiple push destinations are common grounds for Flume.
It is not so nice to use if your data needs external enrichment (taking data from external databases or web services), as transactions and (micro)batches may lead to reprocessing and it relies upon the application to avoid duplicates.

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