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  1. Stackups
  2. DevOps
  3. Log Management
  4. Log Management
  5. Apache Flume vs Filebeat

Apache Flume vs Filebeat

OverviewComparisonAlternatives

Overview

Apache Flume
Apache Flume
Stacks48
Followers120
Votes0
Filebeat
Filebeat
Stacks133
Followers252
Votes0

Apache Flume vs Filebeat: What are the differences?

# Introduction

1. **Architecture**: Apache Flume follows a distributed architecture where data flows from the source to the sink through various channels, whereas Filebeat is designed with an agent-based architecture that collects and forwards log files to Elasticsearch, Logstash, or other outputs.
2. **Flexibility**: Apache Flume supports a wide range of data sources and can be extended through custom components, allowing for more flexibility in data ingestion compared to Filebeat, which is primarily focused on log file collection.
3. **Processing Capability**: Apache Flume provides built-in processing capabilities such as data transformation and enrichment through its various interceptors, while Filebeat is more focused on efficient log file forwarding with minimal processing.
4. **Scalability**: Apache Flume is well-suited for large-scale data ingestion and processing with its distributed and reliable architecture, whereas Filebeat is more suitable for smaller deployments due to its agent-based design.
5. **Monitoring and Management**: Apache Flume offers a web-based monitoring dashboard for real-time monitoring and management of data flows, while Filebeat relies on external tools like Kibana or Logstash for monitoring and management.
6. **Integration**: Apache Flume has built-in support for integrating with Hadoop ecosystem tools like HDFS and HBase, making it a preferred choice for data pipelines involving big data processing, while Filebeat is mainly used for log file shipping to Elasticsearch or Logstash for further analysis.

In Summary, Apache Flume and Filebeat have significant differences in their architecture, flexibility, processing capabilities, scalability, monitoring, management, and integration.

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Detailed Comparison

Apache Flume
Apache Flume
Filebeat
Filebeat

It is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with tunable reliability mechanisms and many failover and recovery mechanisms. It uses a simple extensible data model that allows for online analytic application.

It helps you keep the simple things simple by offering a lightweight way to forward and centralize logs and files.

Statistics
Stacks
48
Stacks
133
Followers
120
Followers
252
Votes
0
Votes
0
Integrations
No integrations available
Logstash
Logstash

What are some alternatives to Apache Flume, Filebeat?

Papertrail

Papertrail

Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.

Logmatic

Logmatic

Get a clear overview of what is happening across your distributed environments, and spot the needle in the haystack in no time. Build dynamic analyses and identify improvements for your software, your user experience and your business.

Loggly

Loggly

It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.

Logentries

Logentries

Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users.

Logstash

Logstash

Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.

Graylog

Graylog

Centralize and aggregate all your log files for 100% visibility. Use our powerful query language to search through terabytes of log data to discover and analyze important information.

Sematext

Sematext

Sematext pulls together performance monitoring, logs, user experience and synthetic monitoring that tools organizations need to troubleshoot performance issues faster.

Fluentd

Fluentd

Fluentd collects events from various data sources and writes them to files, RDBMS, NoSQL, IaaS, SaaS, Hadoop and so on. Fluentd helps you unify your logging infrastructure.

ELK

ELK

It is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.

Sumo Logic

Sumo Logic

Cloud-based machine data analytics platform that enables companies to proactively identify availability and performance issues in their infrastructure, improve their security posture and enhance application rollouts. Companies using Sumo Logic reduce their mean-time-to-resolution by 50% and can save hundreds of thousands of dollars, annually. Customers include Netflix, Medallia, Orange, and GoGo Inflight.

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