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

Apache NiFi

358
692
+ 1
65
Kapacitor

39
54
+ 1
0
Add tool

Apache NiFi vs Kapacitor: 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, Kapacitor is detailed as "A real-time streaming data processing engine". It is a native data processing engine for InfluxDB 1.x and is an integrated component in the InfluxDB 2.0 platform It can process both stream and batch data from InfluxDB, acting on this data in real-time via its programming language TICKscript..

Apache NiFi and Kapacitor can be primarily classified as "Stream Processing" tools.

Manage your open source components, licenses, and vulnerabilities
Learn More
Pros of Apache NiFi
Pros of Kapacitor
  • 17
    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
  • 3
    End-to-end security between all nodes
  • 2
    Built-in graphical user interface
  • 2
    Can handle messages up to gigabytes in size
  • 2
    Data provenance
  • 1
    Lots of documentation
  • 1
    Hbase support
  • 1
    Support for custom Processor in Java
  • 1
    Hive support
  • 1
    Kudu support
  • 1
    Slack integration
  • 1
    Lot of articles
    Be the first to leave a pro

    Sign up to add or upvote prosMake informed product decisions

    Cons of Apache NiFi
    Cons of Kapacitor
    • 2
      HA support is not full fledge
    • 2
      Memory-intensive
    • 1
      Kkk
      Be the first to leave a con

      Sign up to add or upvote consMake informed product decisions

      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 Kapacitor?

      It is a native data processing engine for InfluxDB 1.x and is an integrated component in the InfluxDB 2.0 platform. It can process both stream and batch data from InfluxDB, acting on this data in real-time via its programming language TICKscript.

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

      What companies use Apache NiFi?
      What companies use Kapacitor?
      Manage your open source components, licenses, and vulnerabilities
      Learn More

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

      What tools integrate with Apache NiFi?
      What tools integrate with Kapacitor?

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

      What are some alternatives to Apache NiFi and Kapacitor?
      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