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Apache NiFi

294
599
+ 1
62
StreamSets

46
112
+ 1
0
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Apache NiFi vs StreamSets: 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, StreamSets is detailed as "Where DevOps Meets Data Integration". The industry's first data operations platform for full life-cycle management of data in motion.

Apache NiFi and StreamSets are primarily classified as "Stream Processing" and "Data Science" tools respectively.

Some of the features offered by Apache NiFi are:

  • Web-based user interface
  • Highly configurable
  • Data Provenance

On the other hand, StreamSets provides the following key features:

  • Build Batch & Streaming Pipelines in Hours
  • Map and Monitor Runtime Performance
  • Protect Sensitive Data as it Arrives
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Pros of Apache NiFi
Pros of StreamSets
  • 15
    Visual Data Flows using Directed Acyclic Graphs (DAGs)
  • 8
    Free (Open Source)
  • 7
    Simple-to-use
  • 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 NiFi
    Cons of StreamSets
    • 2
      HA support is not full fledge
    • 2
      Memory-intensive
    • 2
      No user community
    • 1
      Crashes

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    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.

    What is StreamSets?

    An end-to-end data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps.

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

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    What are some alternatives to Apache NiFi and StreamSets?
    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.
    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.
    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.
    See all alternatives