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Apache Flume

Apache Flume


What is Apache Flume?

Apache Flume is a product enabling the flow of logs and other data into a Hadoop environment.

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TrustRadius Insights

Apache Flume is widely recognized for its ability to process log data in near real-time, making it an excellent choice for log ingestion. …
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Product Details

What is Apache Flume?

Apache Flume is a product enabling the flow of logs and other data into a Hadoop environment.

Apache Flume Technical Details

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Reviews and Ratings


Community Insights

TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!

Apache Flume is widely recognized for its ability to process log data in near real-time, making it an excellent choice for log ingestion. Users have found Apache Flume to be highly effective in collecting, aggregating, and moving substantial amounts of log data. Its value goes beyond its free software status, as it has proven to be a valuable tool in enterprise data warehousing. For example, customers have successfully used Apache Flume as a connector to bring near real-time data from Pharmaceutical Machine data directly to HDFS for further processing. Additionally, Apache Flume's streaming ETL capabilities have allowed for efficient data collection from various sources and delivery to multiple destinations.

One of the standout features of Apache Flume is its ability to handle log processing without the need for repetitive pipeline runs, making it particularly useful in this regard. Furthermore, users have praised the software for its scalability, especially when streaming logs generated from online transaction processing applications to other consumer applications for analytical purposes. Apache Flume has also been seamlessly integrated into log acquisition solutions in environments where application log access is challenging. Customers have utilized Apache Flume for end-to-end logging, ensuring comprehensive monitoring coverage.

Another area where Apache Flume has excelled is in handling complex data transfers to Hadoop using HDFS—a task that was previously difficult to achieve. With fast ETL processes facilitated by Apache Flume, users can quickly extract, transform and load data. Some have even leveraged the software's capabilities for downloading marketing data, aiding in the development of effective marketing strategies. Furthermore, Apache Flume has proved invaluable in collecting data for analytics, particularly for new products entering the market.

Another notable use case is how Apache Flume has played a crucial role in generating monthly compliance reports based on log data, ensuring organizational compliance. Additionally, Apache Flume has seamlessly integrated with Change Data Capture systems to ingest near real-time database changes into Kafka. This integration has enabled real-time analysis, machine learning, and dynamic dashboards in Big Data environments. Overall, Apache Flume has proven to be a reliable solution for log ingestion, data transfer, ETL processes, marketing data collection, compliance reporting, and real-time analytics.

Easy Interpretation of Log Data: Users have found Apache Flume to be very easy to interpret log data in near real-time. Several reviewers have mentioned that the user-friendliness and ease of use make it a convenient tool for analyzing logs efficiently.

Support for Multiple Data Sources: The ability of Apache Flume to support data collection from a variety of data sources is highly appreciated by users. Many reviewers have praised its flexibility and integration with other open-source tools, allowing them to collect large volumes of data from multiple applications and systems effortlessly.

Scalability and Reliability: The scalability, reliability, and fault tolerance of Apache Flume are highly valued by users. Numerous reviewers have highlighted its capability to handle large amounts of streaming data, ensuring smooth operations even under heavy loads.

Reliability Issue: Some users have reported that Apache Flume is not as reliable as Apache Kafka. They have experienced issues where missed messages cannot be retrieved, leading to potential data loss and impacting the integrity of their data processing workflows.

Large Footprint: Users find the software to have a significant footprint with an excessive number of lines of Java code. This can make it resource-intensive and impact system performance, requiring more computational resources and potentially limiting scalability.

Lack of New Features: Reviewers believe that Apache Flume needs to evolve more and include new features periodically, similar to paid software. The lack of regular updates and additions can limit its capabilities for handling diverse data processing requirements, hindering its ability to adapt to changing business needs.

Based on user reviews, the following recommendations for Apache Flume are commonly mentioned:

  • Users suggest that Apache Flume is well-suited for simple data transformations during streaming from source to sink.
  • If fault tolerance and data persistence are crucial factors in a streaming application, it is recommended to consider alternatives such as Apache Kafka, Splunk, or Apache NiFi.
  • Some users note that Apache Flume has a relatively high learning curve. Therefore, newcomers may need to invest additional time and effort to become proficient in using the software effectively.

Attribute Ratings


(1-2 of 2)
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Score 8 out of 10
Vetted Review
Verified User
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.
  • 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).
  • Positive impact on ROI due to a reduction in manual labor to generate and maintain compliance reports based on logs.
  • Positive impact on the business objective by reducing the need for provisioning compute for log aggregate IT stack in advance but adding on an as-needed basis.
Apache Flume is on par with Scribe with similar functions. Apache Kafka is a generation purpose while Apache Flume is specific to log aggregation. Google Pub/Sub and IBM MQ are costlier than Apache Flume ( open source ) and have a lot more cost associated with them. Apama Streaming Analytics and Tibco Steaming are more comprehensive streaming solutions than Apache Flume so for deeper performance guarantees, it is easier to use Apache Flume.
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.
Juan Francisco Tavira | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
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.
  • 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
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.
  • Flume has simplified a lot many of our ingest procedures, easier to deploy and integrate than a classical EAI, reducing the time to market
  • But opposed to EAIs if the project starts to grow in complexity Apache Flume project may not be as suitable
Apache Flume is a very good solution when your project is not very complex at transformation and enrichment, and good if you have an external management suite like Cloudera, Hortonworks, etc. But it is not a real EAI or ETL like AB Initio or Attunity so you need to know exactly what you want.
On the other hand being an opensource project give Apache a lot of room to personalize thanks to its plug-able architecture and has a very nice performance having a very low CPU and Memory footprint, a single server can do the job on many occasions, as opposed to the multi-server architecture of paid products.
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