Apache Flume vs Apache NiFi

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Apache Flume

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Apache NiFi

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Pros of Apache Flume
Pros of Apache NiFi
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    • 15
      Visual Data Flows using Directed Acyclic Graphs (DAGs)
    • 8
      Free (Open Source)
    • 7
    • 5
      Reactive with back-pressure
    • 5
      Scalable horizontally as well as vertically
    • 4
      Fast prototyping
    • 3
      Bi-directional channels
    • 2
      Data provenance
    • 2
      Built-in graphical user interface
    • 2
      End-to-end security between all nodes
    • 2
      Can handle messages up to gigabytes in size
    • 1
      Hbase support
    • 1
      Kudu support
    • 1
      Hive support
    • 1
      Slack integration
    • 1
      Support for custom Processor in Java
    • 1
      Lot of articles
    • 1
      Lots of documentation

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    Cons of Apache Flume
    Cons of Apache NiFi
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      • 2
        HA support is not full fledge
      • 2

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      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 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.

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      Jobs that mention Apache Flume and Apache NiFi as a desired skillset
      United States of America Texas Richardson
      United Kingdom of Great Britain and Northern Ireland England Feltham
      What companies use Apache Flume?
      What companies use Apache NiFi?
      See which teams inside your own company are using Apache Flume or Apache NiFi.
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      What tools integrate with Apache Flume?
      What tools integrate with Apache NiFi?
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        What are some alternatives to Apache Flume and Apache NiFi?
        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.
        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 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 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.
        See all alternatives