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  1. Stackups
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  4. Stream Processing
  5. Apache Storm vs Kapacitor

Apache Storm vs Kapacitor

OverviewComparisonAlternatives

Overview

Apache Storm
Apache Storm
Stacks207
Followers282
Votes25
GitHub Stars6.7K
Forks4.1K
Kapacitor
Kapacitor
Stacks40
Followers54
Votes0

Apache Storm vs Kapacitor: What are the differences?

What is Apache Storm? Distributed and fault-tolerant realtime computation. 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.

What is Kapacitor? 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 Storm and Kapacitor can be primarily classified as "Stream Processing" tools.

Apache Storm is an open source tool with 5.81K GitHub stars and 3.94K GitHub forks. Here's a link to Apache Storm's open source repository on GitHub.

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Detailed Comparison

Apache Storm
Apache Storm
Kapacitor
Kapacitor

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.

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.

Storm integrates with the queueing and database technologies you already use;Simple API;Scalable;Fault tolerant;Guarantees data processing;Use with any language;Easy to deploy and operate;Free and open source
can process both stream and batch data ; acting on data in real-time
Statistics
GitHub Stars
6.7K
GitHub Stars
-
GitHub Forks
4.1K
GitHub Forks
-
Stacks
207
Stacks
40
Followers
282
Followers
54
Votes
25
Votes
0
Pros & Cons
Pros
  • 10
    Flexible
  • 6
    Easy setup
  • 4
    Event Processing
  • 3
    Clojure
  • 2
    Real Time
No community feedback yet
Integrations
No integrations available
InfluxDB
InfluxDB
Kafka
Kafka

What are some alternatives to Apache Storm, Kapacitor?

Apache NiFi

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.

Confluent

Confluent

It is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream

KSQL

KSQL

KSQL is an open source streaming SQL engine for Apache Kafka. It provides a simple and completely interactive SQL interface for stream processing on Kafka; no need to write code in a programming language such as Java or Python. KSQL is open-source (Apache 2.0 licensed), distributed, scalable, reliable, and real-time.

Heron

Heron

Heron is realtime analytics platform developed by Twitter. It is the direct successor of Apache Storm, built to be backwards compatible with Storm's topology API but with a wide array of architectural improvements.

Kafka Streams

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.

Redpanda

Redpanda

It is a streaming platform for mission critical workloads. Kafka® compatible, No Zookeeper®, no JVM, and no code changes required. Use all your favorite open source tooling - 10x faster.

Faust

Faust

It is a stream processing library, porting the ideas from Kafka Streams to Python. It provides both stream processing and event processing, sharing similarity with tools such as Kafka Streams, Apache Spark/Storm/Samza/Flink.

Samza

Samza

It allows you to build stateful applications that process data in real-time from multiple sources including Apache Kafka.

Benthos

Benthos

It is a high performance and resilient stream processor, able to connect various sources and sinks in a range of brokering patterns and perform hydration, enrichments, transformations and filters on payloads.

Amazon WorkSpaces Streaming Protocol

Amazon WorkSpaces Streaming Protocol

It is a cloud-native streaming protocol that enables a consistent user experience when accessing your end user’s WorkSpaces across global distances and unreliable networks. It also enables additional features such as the beta feature of bi-directional video. As a cloud-native protocol, it delivers feature and performance enhancements without manual updates on your WorkSpaces.

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