Apache Flume vs Logstash

Need advice about which tool to choose?Ask the StackShare community!

Apache Flume

41
102
+ 1
0
Logstash

9.5K
7.2K
+ 1
102
Add tool

Apache Flume vs Logstash: What are the differences?

Developers describe Apache Flume as "A service for collecting, aggregating, and moving large amounts of log data". 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. On the other hand, Logstash is detailed as "Collect, Parse, & Enrich Data". 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.

Apache Flume and Logstash belong to "Log Management" category of the tech stack.

Logstash is an open source tool with 10.4K GitHub stars and 2.81K GitHub forks. Here's a link to Logstash's open source repository on GitHub.

Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn More
Pros of Apache Flume
Pros of Logstash
    Be the first to leave a pro
    • 68
      Free
    • 18
      Easy but powerful filtering
    • 12
      Scalable
    • 2
      Kibana provides machine learning based analytics to log
    • 1
      Great to meet GDPR goals
    • 1
      Well Documented

    Sign up to add or upvote prosMake informed product decisions

    Cons of Apache Flume
    Cons of Logstash
      Be the first to leave a con
      • 4
        Memory-intensive
      • 1
        Documentation difficult to use

      Sign up to add or upvote consMake informed product decisions

      No Stats
      - No public GitHub repository available -

      What is Apache Flume?

      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.

      What is 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.

      Need advice about which tool to choose?Ask the StackShare community!

      Jobs that mention Apache Flume and Logstash as a desired skillset
      CBRE
      United States of America Texas Richardson
      CBRE
      United Kingdom of Great Britain and Northern Ireland England Feltham
      What companies use Apache Flume?
      What companies use Logstash?
      See which teams inside your own company are using Apache Flume or Logstash.
      Sign up for StackShare EnterpriseLearn More

      Sign up to get full access to all the companiesMake informed product decisions

      What tools integrate with Apache Flume?
      What tools integrate with Logstash?
        No integrations found

        Sign up to get full access to all the tool integrationsMake informed product decisions

        Blog Posts

        May 21 2019 at 12:20AM

        Elastic

        ElasticsearchKibanaLogstash+4
        12
        3836
        GitHubPythonReact+42
        48
        39830
        GitHubMySQLSlack+44
        109
        50315
        What are some alternatives to Apache Flume and Logstash?
        Apache Spark
        Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
        Apache Storm
        Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.
        Kafka
        Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
        Apache Flink
        Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
        Apache NiFi
        An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.
        See all alternatives