Apache Flume vs Rsyslog

Overview

Rsyslog

Stacks37

Followers75

Votes0

GitHub Stars2.2K

Forks700

Apache Flume

Stacks48

Followers120

Votes0

Apache Flume vs Rsyslog: What are the differences?

Scalability: Apache Flume is designed for high scalability and can handle large volumes of data efficiently. It can distribute data across multiple nodes and support load balancing, which makes it suitable for big data processing. On the other hand, Rsyslog is primarily built for smaller scale deployments and may not perform as well with large amounts of data.
Flexibility: Apache Flume provides a flexible and extensible architecture, allowing users to customize and extend its functionalities based on specific requirements. It supports various sources, sinks, and channel types, providing a wide range of options for data ingestion and processing. Rsyslog, on the other hand, offers limited flexibility in terms of data sources and lacks the extensive plugin ecosystem of Flume.
Reliability: Apache Flume ensures data reliability through built-in mechanisms like transactional semantics and guaranteed delivery. It can handle failures and recover from them without data loss. In contrast, Rsyslog may not provide the same level of reliability, especially in scenarios where data loss can be critical.
Compatibility: Apache Flume is built with a focus on compatibility with Hadoop ecosystem components, such as HDFS and HBase. It seamlessly integrates with these components, allowing users to easily ingest data into Hadoop clusters. Rsyslog, on the other hand, is not specifically designed for Hadoop integration and may require additional configuration and setup for such use cases.
Ease of Use: Apache Flume provides a user-friendly interface and configuration options, making it relatively easy to set up and operate. It offers monitoring and management tools, along with a web-based graphical user interface (GUI), facilitating easier administration. Rsyslog, although relatively straightforward to install and configure, may require more manual setup and lacks the same level of user-friendly management tools.
Community Support: Apache Flume benefits from a large and active open-source community that contributes to its development, documentation, and troubleshooting. This strong community support ensures a wealth of resources, including forums, tutorials, and plugins. Rsyslog community, while active in its own right, may not have the same breadth and depth of resources available.

In summary, Apache Flume offers high scalability, flexibility, reliability, compatibility with Hadoop, ease of use, and strong community support, while Rsyslog may have limitations in these areas.

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Detailed Comparison

Rsyslog	Apache Flume
It offers high-performance, great security features and a modular design. It is able to accept inputs from a wide variety of sources, transform them, and output to the results to diverse destinations.	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.
Multi-threading; TCP, SSL, TLS, RELP; MySQL, PostgreSQL, Oracle and more; Filter any part of syslog message;	-
Statistics
GitHub Stars 2.2K	GitHub Stars -
GitHub Forks 700	GitHub Forks -
Stacks 37	Stacks 48
Followers 75	Followers 120
Votes 0	Votes 0
Integrations
Oracle PostgreSQL Splunk MySQL	No integrations available

What are some alternatives to Rsyslog, Apache Flume?

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

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

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 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 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

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

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

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

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.

Related Comparisons

Apache Flume vs Rsyslog: What are the differences?

Scalability: Apache Flume is designed for high scalability and can handle large volumes of data efficiently. It can distribute data across multiple nodes and support load balancing, which makes it suitable for big data processing. On the other hand, Rsyslog is primarily built for smaller scale deployments and may not perform as well with large amounts of data.
Flexibility: Apache Flume provides a flexible and extensible architecture, allowing users to customize and extend its functionalities based on specific requirements. It supports various sources, sinks, and channel types, providing a wide range of options for data ingestion and processing. Rsyslog, on the other hand, offers limited flexibility in terms of data sources and lacks the extensive plugin ecosystem of Flume.
Reliability: Apache Flume ensures data reliability through built-in mechanisms like transactional semantics and guaranteed delivery. It can handle failures and recover from them without data loss. In contrast, Rsyslog may not provide the same level of reliability, especially in scenarios where data loss can be critical.
Compatibility: Apache Flume is built with a focus on compatibility with Hadoop ecosystem components, such as HDFS and HBase. It seamlessly integrates with these components, allowing users to easily ingest data into Hadoop clusters. Rsyslog, on the other hand, is not specifically designed for Hadoop integration and may require additional configuration and setup for such use cases.
Ease of Use: Apache Flume provides a user-friendly interface and configuration options, making it relatively easy to set up and operate. It offers monitoring and management tools, along with a web-based graphical user interface (GUI), facilitating easier administration. Rsyslog, although relatively straightforward to install and configure, may require more manual setup and lacks the same level of user-friendly management tools.
Community Support: Apache Flume benefits from a large and active open-source community that contributes to its development, documentation, and troubleshooting. This strong community support ensures a wealth of resources, including forums, tutorials, and plugins. Rsyslog community, while active in its own right, may not have the same breadth and depth of resources available.

In summary, Apache Flume offers high scalability, flexibility, reliability, compatibility with Hadoop, ease of use, and strong community support, while Rsyslog may have limitations in these areas.

Apache Flume vs Rsyslog

Overview