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Apache Flink VS Azure Machine Learning Studio

Compare Apache Flink VS Azure Machine Learning Studio 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.

Azure Machine Learning Studio logo Azure Machine Learning Studio

Azure Machine Learning Studio is a GUI-based integrated development environment for constructing and operationalizing Machine Learning workflow on Azure.
  • Apache Flink Landing page
    Landing page //
    2023-10-03
  • Azure Machine Learning Studio Landing page
    Landing page //
    2021-08-03

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

Azure Machine Learning Studio videos

Azure Machine Learning Studio

More videos:

  • Review - Introduction to Microsoft Azure Machine Learning Studio & Services

Category Popularity

0-100% (relative to Apache Flink and Azure Machine Learning Studio)
Big Data
100 100%
0% 0
Data Science And Machine Learning
Stream Processing
100 100%
0% 0
Machine Learning
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Apache Flink seems to be a lot more popular than Azure Machine Learning Studio. While we know about 29 links to Apache Flink, we've tracked only 2 mentions of Azure Machine Learning Studio. 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

Azure Machine Learning Studio mentions (2)

  • What are all possible FREE Machine Learning integrations with Power BI?
    Machine Learning studio https://studio.azureml.net/ but this will be discontinued in Dec 01,2021 :(. Source: over 2 years ago
  • Stumbling into BI as a job role and need advice
    Advanced analytics, predictive modeling: You can't go passed learning R or Python if you're that way inclined.. however, if you're a GUI monkey like me, I have had a fair amount of success using https://studio.azureml.net/ it's free at base level :). Source: almost 3 years ago

What are some alternatives?

When comparing Apache Flink and Azure Machine Learning Studio, 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.

IBM Watson Studio - Learn more about Watson Studio. Increase productivity by giving your team a single environment to work with the best of open source and IBM software, to build and deploy an AI solution.

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

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

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

Pega Platform - The best-in-class, rapid no-code Pega Platform is unified for building BPM, CRM, case management, and real-time decisioning apps.