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Apache Flink VS AWS IoT Core

Compare Apache Flink VS AWS IoT Core and see what are their differences

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Apache Flink logo Apache Flink

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

AWS IoT Core logo AWS IoT Core

Whether building a connected home application for home security or building an industrial application to proactively identify equipment breakdown, you can use AWS IoT Core to securely communicate with and gather data from your diverse fleet of IoT d…
  • Apache Flink Landing page
    Landing page //
    2023-10-03
  • AWS IoT Core Landing page
    Landing page //
    2022-02-05

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.

AWS IoT Core features and specs

  • Scalability
    AWS IoT Core can automatically scale to accommodate billions of devices and trillions of messages, making it suitable for both small and large IoT deployments.
  • Integration with AWS Services
    Seamlessly integrates with other AWS services, such as AWS Lambda, Amazon S3, and Amazon DynamoDB, allowing for complex workflows and data processing.
  • Security
    Provides robust security features including mutual authentication, end-to-end encryption, and fine-grained access control to protect data.
  • Device Management
    Offers features for managing device fleets, such as registering devices, managing permissions, and monitoring connectivity status.
  • MQTT Support
    Supports the popular MQTT protocol, which is lightweight and ideal for connecting remote devices with minimal bandwidth.
  • Serverless Architecture
    Supports a serverless approach, which reduces the need for infrastructure management and allows developers to focus more on building applications.

Possible disadvantages of AWS IoT Core

  • Complex Pricing
    The pricing structure can be complex, involving costs for messaging, data transfer, and other AWS services, which can make it challenging to estimate costs accurately.
  • Steep Learning Curve
    The platform's extensive features and broad integration options can be overwhelming for new users or those unfamiliar with AWS services.
  • Vendor Lock-in
    Using AWS IoT Core can lead to potential vendor lock-in due to the deep integration with the broader suite of AWS services.
  • Latency
    Depending on the geographical location of devices and nearest AWS regions, there may be concerns about latency for time-sensitive applications.
  • Limited Offline Capabilities
    Primarily designed for cloud connectivity, so offline capabilities might require additional configuration or third-party solutions.

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

AWS IoT Core videos

+ Add

Getting Started with AWS IoT Core for LoRaWAN

More videos:

  • Review - How can I start publishing messages to AWS IoT Core from my device?

Category Popularity

0-100% (relative to Apache Flink and AWS IoT Core)

Apache Flink

AWS IoT Core

Big Data
100 100%
Big Data
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Stream Processing
100 100%
Stream Processing
0% 0
Analytics
0 0%
Analytics
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 AWS IoT Core

Apache Flink Reviews

We have no reviews of Apache Flink yet.
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AWS IoT Core Reviews

Open Source Internet of Things (IoT) Platforms
It is a managed cloud service. AWS IoT Core will allow devices to connect with the cloud and interact with the other devices and cloud applications. It provides support for HTTP, lightweight communication protocol, and MQTT.
Source: jansutris10.medium.com
14 of the Best IoT Platforms to Watch in 2021
AWS IoT Core is a behemoth in IoT platforms, and is the backbone of many fascinating projects such as Expedia, AirBnB, and CoinBase. With support for device software such as FreeRTOS and AWS IoT Greengrass, AWS IoT Core encompasses a vastly superior ecosystem of products allowing development in smart homes and industrial automation. All AWS data is visualized on an AWS IoT...
Source: www.iottechtrends.com

Social recommendations and mentions

Based on our record, Apache Flink should be more popular than AWS IoT Core. It has been mentiond 41 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.

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 / 4 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 / 17 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 / 22 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 / 27 days 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

AWS IoT Core mentions (9)

  • AWS AppSync Events vs IoT Core
    AWS recently announced AppSync Events and it looks like very useful service. However when I was reading about it, it just felt like this is "just" a layer on top of IoT Core which exists for many years. Let's find out if this is the case... - Source: dev.to / 6 months ago
  • WebSockets, gRPC, MQTT, and SSE - Which Real-Time Notification Method Is For You?
    MQTT - AWS IoT Core offers a managed MQTT message broker, giving you easy access to your devices. Fun fact, this is what powers the notifications in Serverlesspresso. - Source: dev.to / over 1 year ago
  • Serverless Facial Recognition Voting Application Using AWS Services
    AWS IoT: For real-time communication between the server and the frontend application. - Source: dev.to / about 2 years ago
  • Building Serverlesspresso
    AWS IoT Core is a service that allows you to connect your devices securely to the AWS cloud and with ease. Option for device management, data processing as well as integration with other AWS services is provided. Click here for more on AWS IoT Core. - Source: dev.to / about 2 years ago
  • Use EventBridge to handle API requests
    From here you can do all sorts of actions. For example, the serverless-coffee project used IOT Core. With IOT Core you can notify the end-user with status updates. And notify the barista that what kind of coffee needs to be created. - Source: dev.to / about 2 years ago
View more

What are some alternatives?

When comparing Apache Flink and AWS IoT Core, 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.

AWS IoT - Easily and securely connect devices to the cloud.

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

Particle.io - Particle is an IoT platform enabling businesses to build, connect and manage their connected solutions.

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

Blynk.io - We make internet of things simple

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