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Apache Flink VS Ansible Semaphore

Compare Apache Flink VS Ansible Semaphore and see what are their differences

Apache Flink logo Apache Flink

Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

Ansible Semaphore logo Ansible Semaphore

Modern UI for Ansible
  • Apache Flink Landing page
    Landing page //
    2023-10-03
  • Ansible Semaphore Landing page
    Landing page //
    2022-10-09

If your project has grown and deploying from the terminal is no longer for you then Ansible Semaphore is what you need.

Apache Flink videos

GOTO 2019 • Introduction to Stateful Stream Processing with Apache Flink • Robert Metzger

More videos:

  • Tutorial - Apache Flink Tutorial | Flink vs Spark | Real Time Analytics Using Flink | Apache Flink Training
  • Tutorial - How to build a modern stream processor: The science behind Apache Flink - Stefan Richter

Ansible Semaphore videos

Ansible Semaphore - Modern Ansible UI

Category Popularity

0-100% (relative to Apache Flink and Ansible Semaphore)
Big Data
100 100%
0% 0
DevOps Tools
0 0%
100% 100
Stream Processing
100 100%
0% 0
Continuous Integration
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Flink and Ansible Semaphore

Apache Flink Reviews

We have no reviews of Apache Flink yet.
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Ansible Semaphore Reviews

  1. Lightweight alternative for AWX

    Use Semaphore 3+ years, very stable, useful and lightweight. No need Docker.

    🏁 Competitors: AWX, RunDeck

Social recommendations and mentions

Based on our record, Apache Flink seems to be a lot more popular than Ansible Semaphore. While we know about 29 links to Apache Flink, we've tracked only 2 mentions of Ansible Semaphore. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Apache Flink mentions (29)

  • Array Expansion in Flink SQL
    I’ve recently started my journey with Apache Flink. As I learn certain concepts, I’d like to share them. One such "learning" is the expansion of array type columns in Flink SQL. Having used ksqlDB in a previous life, I was looking for functionality similar to the EXPLODE function to "flatten" a collection type column into a row per element of the collection. Because Flink SQL is ANSI compliant, it’s no surprise... - Source: dev.to / 1 day ago
  • Show HN: An SQS Alternative on Postgres
    You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / 15 days ago
  • Top 10 Common Data Engineers and Scientists Pain Points in 2024
    Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / about 1 month ago
  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 3 months ago
  • Go concurrency simplified. Part 4: Post office as a data pipeline
    Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 5 months ago
View more

Ansible Semaphore mentions (2)

  • Need User interface for managing and running the ansible playbooks.
    Once you have tower or awx you can throw away jenkins. No more silliness of groovy and java when you have python and ssh based actions For UI try Semaphore - https://github.com/ansible-semaphore/semaphore. Source: over 2 years ago
  • Automatic softwaredeployment & installation/updating Tool
    Googled and found this: https://github.com/ansible-semaphore/semaphore. Source: over 2 years ago

What are some alternatives?

When comparing Apache Flink and Ansible Semaphore, you can also consider the following products

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

RunDeck - RunDeck is an open source automation service with a web console, command line tools and a WebAPI.

Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.

AWX - Centralize and control your IT infrastructure with a visual dashboard

Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.

Ansible tower - An ansible web frontend.