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IBM MQ VS Apache Flink

Compare IBM MQ VS Apache Flink and see what are their differences

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IBM MQ logo IBM MQ

IBM MQ is messaging middleware that simplifies and accelerates the integration of diverse applications and data across multiple platforms.

Apache Flink logo Apache Flink

Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
  • IBM MQ Landing page
    Landing page //
    2023-07-03
  • Apache Flink Landing page
    Landing page //
    2023-10-03

IBM MQ videos

+ Add

IBM MQ Clustering - Tom Dunlap

More videos:

  • Review - IBM Blockchain Platform - 2019 Review - All You Need to Know
  • Review - IBM MQ V9 Open Source Monitoring
  • Review - IBM Blockchain Platform Community Call – Next Generation Platform Tour + Q&A
  • Review - The next generation of the IBM Blockchain Platform

Apache Flink videos

+ Add

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

Category Popularity

0-100% (relative to IBM MQ and Apache Flink)

IBM MQ

Apache Flink

Cloud Computing
100 100%
Cloud Computing
0% 0
Big Data
0 0%
Big Data
100% 100
Data Integration
100 100%
Data Integration
0% 0
Stream Processing
0 0%
Stream Processing
100% 100

User comments

Share your experience with using IBM MQ and Apache Flink. For example, how are they different and which one is better?
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Reviews

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

IBM MQ Reviews

6 Best Kafka Alternatives: 2022’s Must-know List
IBM MQ is one of the best Kafka Alternatives which has an easy-to-use Interface and High Reliability and Data Security. It also facilitates the interoperability between various applications, either within or outside the organization. IBM MQ allows developers to focus on critical issues and manage any changes to transaction volumes asynchronously due to its simple structure.
Source: hevodata.com
Top 15 Alternatives to RabbitMQ In 2021
IBM MQ is an official message middleware which shortens the integration of varied applications and data spread throughout numerous platforms. It employs a message queue to share the info and offers a distinct messaging service for cloud systems, IoT gadgets, and mobile environments. By linking every element virtually from modest device to most complicated industrial...
Source: gokicker.com
Top 15 Kafka Alternatives Popular In 2021
IBM MQ is an easily usable interface with a great deal of reliability and security. Support is readily available in case needed anytime. It looks at handling the interoperability between various applications, be it within the organization or outside. It has asynchronous competencies and offers message integrity and relentless delivery. Because of its simplistic nature, it...
Source: www.spec-india.com

Apache Flink Reviews

We have no reviews of Apache Flink yet.
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Social recommendations and mentions

Based on our record, Apache Flink seems to be more popular. It has been mentiond 27 times since March 2021. 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.

IBM MQ mentions (0)

We have not tracked any mentions of IBM MQ yet. Tracking of IBM MQ recommendations started around Mar 2021.

Apache Flink mentions (27)

  • 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 / 24 days 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
  • Five Apache projects you probably didn't know about
    Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago
  • Getting Started with Flink SQL, Apache Iceberg and DynamoDB Catalog
    Due to the technology transformation we want to do recently, we started to investigate Apache Iceberg. In addition, the data processing engine we use in house is Apache Flink, so it's only fair to look for an experimental environment that integrates Flink and Iceberg. - Source: dev.to / 5 months ago
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What are some alternatives?

When comparing IBM MQ and Apache Flink, you can also consider the following products

RabbitMQ - RabbitMQ is an open source message broker software.

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

Ethereum - Ethereum is a decentralized platform for applications that run exactly as programmed without any chance of fraud, censorship or third-party interference.

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

Hyperledger - Hyperledger is a multi-project open source collaborative effort hosted by The Linux Foundation, created to advance cross-industry blockchain technologies.

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

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