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A real-time streaming data processing engine

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.
Kapacitor is a tool in the Stream Processing category of a tech stack.

Who uses Kapacitor?

7 companies reportedly use Kapacitor in their tech stacks, including Entelo, Veris, and Zencom.

11 developers on StackShare have stated that they use Kapacitor.

Kapacitor Integrations

Why developers like Kapacitor?

Here’s a list of reasons why companies and developers use Kapacitor
Top Reasons
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Kapacitor's Features

  • can process both stream and batch data
  • acting on data in real-time

Kapacitor Alternatives & Comparisons

What are some alternatives to Kapacitor?
Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.
Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
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 Streams
It is a client library for building applications and microservices, where the input and output data are stored in Kafka clusters. It combines the simplicity of writing and deploying standard Java and Scala applications on the client side with the benefits of Kafka's server-side cluster technology.
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Kapacitor's Followers
20 developers follow Kapacitor to keep up with related blogs and decisions.
Gregory Scafarto
Alberto Segarra Martinez
abi s
Sunil Matham
瑞光 裴
Darpan Thanki
Radosław Osiński