Software Alternatives, Accelerators & Startups

Apache Flink VS .NET for Apache Spark

Compare Apache Flink VS .NET for Apache Spark 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.

.NET for Apache Spark logo .NET for Apache Spark

.NET for Apache Spark™ provides C# and F# language bindings for the Apache Spark distributed data analytics engine. Supported on Linux, macOS, and Windows.
  • Apache Flink Landing page
    Landing page //
    2023-10-03
  • .NET for Apache Spark Landing page
    Landing page //
    2023-05-23

Apache Flink features and specs

  • Real-time Stream Processing
    Apache Flink is designed for real-time data streaming, offering low-latency processing capabilities that are essential for applications requiring immediate data insights.
  • Event Time Processing
    Flink supports event time processing, which allows it to handle out-of-order events effectively and provide accurate results based on the time events actually occurred rather than when they were processed.
  • State Management
    Flink provides robust state management features, making it easier to maintain and query state across distributed nodes, which is crucial for managing long-running applications.
  • Fault Tolerance
    The framework includes built-in mechanisms for fault tolerance, such as consistent checkpoints and savepoints, ensuring high reliability and data consistency even in the case of failures.
  • Scalability
    Apache Flink is highly scalable, capable of handling both batch and stream processing workloads across a distributed cluster, making it suitable for large-scale data processing tasks.
  • Rich Ecosystem
    Flink has a rich set of APIs and integrations with other big data tools, such as Apache Kafka, Apache Hadoop, and Apache Cassandra, enhancing its versatility and ease of integration into existing data pipelines.

Possible disadvantages of Apache Flink

  • Complexity
    Flink’s advanced features and capabilities come with a steep learning curve, making it more challenging to set up and use compared to simpler stream processing frameworks.
  • Resource Intensive
    The framework can be resource-intensive, requiring substantial memory and CPU resources for optimal performance, which might be a concern for smaller setups or cost-sensitive environments.
  • Community Support
    While growing, the community around Apache Flink is not as large or mature as some other big data frameworks like Apache Spark, potentially limiting the availability of community-contributed resources and support.
  • Ecosystem Maturity
    Despite its integrations, the Flink ecosystem is still maturing, and certain tools and plugins may not be as developed or stable as those available for more established frameworks.
  • Operational Overhead
    Running and maintaining a Flink cluster can involve significant operational overhead, including monitoring, scaling, and troubleshooting, which might require a dedicated team or additional expertise.

.NET for Apache Spark features and specs

No features have been listed yet.

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

.NET for Apache Spark videos

No .NET for Apache Spark videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Apache Flink and .NET for Apache Spark)
Big Data
100 100%
0% 0
PHP Web Framework
0 0%
100% 100
Stream Processing
100 100%
0% 0
Data Integration
0 0%
100% 100

User comments

Share your experience with using Apache Flink and .NET for Apache Spark. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, Apache Flink seems to be a lot more popular than .NET for Apache Spark. While we know about 41 links to Apache Flink, we've tracked only 3 mentions of .NET for Apache Spark. 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 (41)

  • What is Apache Flink? Exploring Its Open Source Business Model, Funding, and Community
    Continuous Learning: Leverage online tutorials from the official Flink website and attend webinars for deeper insights. - Source: dev.to / 7 days ago
  • Is RisingWave the Next Apache Flink?
    Apache Flink, known initially as Stratosphere, is a distributed stream processing engine initiated by a group of researchers at TU Berlin. Since its initial release in May 2011, Flink has gained immense popularity in both academia and industry. And it is currently the most well-known streaming system globally (challenge me if you think I got it wrong!). - Source: dev.to / 21 days ago
  • Every Database Will Support Iceberg — Here's Why
    Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave — can read and/or write Iceberg data directly. - Source: dev.to / 25 days ago
  • RisingWave Turns Four: Our Journey Beyond Democratizing Stream Processing
    The last decade saw the rise of open-source frameworks like Apache Flink, Spark Streaming, and Apache Samza. These offered more flexibility but still demanded significant engineering muscle to run effectively at scale. Companies using them often needed specialized stream processing engineers just to manage internal state, tune performance, and handle the day-to-day operational challenges. The barrier to entry... - Source: dev.to / about 1 month ago
  • Twitter's 600-Tweet Daily Limit Crisis: Soaring GCP Costs and the Open Source Fix Elon Musk Ignored
    Apache Flink: Flink is a unified streaming and batching platform developed under the Apache Foundation. It provides support for Java API and a SQL interface. Flink boasts a large ecosystem and can seamlessly integrate with various services, including Kafka, Pulsar, HDFS, Iceberg, Hudi, and other systems. - Source: dev.to / about 1 month ago
View more

.NET for Apache Spark mentions (3)

  • Debug dotnet Spark using Databricks-connect
    I assume you are talking about this https://dotnet.microsoft.com/en-us/apps/data/spark. Source: over 2 years ago
  • Microsoft Announces new Scalable Machine Learning Library for .NET
    Good question! The API and the authoring experience is .NET, but the backend is Apache Spark which is built on the JVM. We use the .NET for Apache Spark to do the parallization. Source: almost 3 years ago
  • Microsoft Announces new Scalable Machine Learning Library for .NET
    Yes that's correct. SynapseML builds on top of the Apache Spark for .NET project which provides .NET support for the Apache Spark distributed computing framework. Apache Spark is written in Scala (a language on the JVM) but has language bindings in Python, R, .NET and other languages. This release adds full .NET language support for all of the models and learners in the SynapseML library so you can author... Source: almost 3 years ago

What are some alternatives?

When comparing Apache Flink and .NET for Apache Spark, 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.

Apache Flume - Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data

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

Vertica - Vertica is a grid-based, column-oriented database designed to manage large, fast-growing volumes of...

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

Printopia - Printopia is a wireless printing application that allows users to print anything directly from their iPhone or iPad.