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Apache NiFi

260
528
+ 1
62
Logstash

8.1K
6.1K
+ 1
102
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Apache NiFi vs Logstash: What are the differences?

Developers describe Apache NiFi as "A reliable system to process and distribute data". 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. 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 NiFi can be classified as a tool in the "Stream Processing" category, while Logstash is grouped under "Log Management".

Logstash is an open source tool with 10.3K GitHub stars and 2.78K GitHub forks. Here's a link to Logstash's open source repository on GitHub.

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Pros of Apache NiFi
Pros of Logstash
  • 15
    Visual Data Flows using Directed Acyclic Graphs (DAGs)
  • 8
    Free (Open Source)
  • 7
    Simple-to-use
  • 5
    Scalable horizontally as well as vertically
  • 5
    Reactive with back-pressure
  • 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
  • 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

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Cons of Apache NiFi
Cons of Logstash
  • 2
    HA support is not full fledge
  • 2
    Memory-intensive
  • 3
    Memory-intensive
  • 1
    Documentation difficult to use

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What companies use Apache NiFi?
What companies use Logstash?
See which teams inside your own company are using Apache NiFi or Logstash.
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What tools integrate with Apache NiFi?
What tools integrate with Logstash?

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What are some alternatives to Apache NiFi and Logstash?
Kafka
Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
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.
Apache Camel
An open source Java framework that focuses on making integration easier and more accessible to developers.
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.
Airflow
Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
See all alternatives