Software Alternatives, Accelerators & Startups

Apache Flink VS Heroku

Compare Apache Flink VS Heroku 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.

Heroku logo Heroku

Agile deployment platform for Ruby, Node.js, Clojure, Java, Python, and Scala. Setup takes only minutes and deploys are instant through git. Leave tedious server maintenance to Heroku and focus on your code.
  • Apache Flink Landing page
    Landing page //
    2023-10-03
  • Heroku Landing page
    Landing page //
    2023-10-05

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.

Heroku features and specs

  • Ease of Use
    Heroku offers an extremely user-friendly interface and a high level of abstraction, making it easy for developers to deploy, manage, and scale applications without worrying about the underlying infrastructure.
  • Quick Deployment
    One of Heroku’s strongest points is the ability to deploy applications quickly using Git. Developers can push their code to Heroku with a simple command, streamlining the entire process.
  • Scalability
    Heroku provides effortless scaling options by allowing developers to add more dynos (containers) with a single command to handle increased traffic and workload.
  • Add-Ons Ecosystem
    Heroku offers a rich ecosystem of add-ons, such as databases, caching, monitoring, and more, which can be easily integrated into applications to extend their functionality.
  • Automatic Updates
    Heroku automatically handles operating system and server updates, allowing developers to focus solely on their application code rather than maintenance tasks.
  • Free Tier
    Heroku offers a free tier with sufficient resources to host small projects and learn the platform without incurring costs, making it accessible for beginners and small-scale applications.

Possible disadvantages of Heroku

  • Cost
    While Heroku offers a free tier, the costs can quickly add up for larger applications and professional use. Paid plans and additional dynos or add-ons can become expensive.
  • Performance
    Heroku’s performance can sometimes be suboptimal compared to other cloud providers, particularly when running high-performance or resource-intensive applications.
  • Limited Control
    Heroku abstracts away a lot of infrastructure management, which can be a downside for developers who need fine-grained control over their environments and configurations.
  • Dyno Sleeping
    Applications running on Heroku’s free tier experience 'dyno sleeping,' where the application goes to sleep after 30 minutes of inactivity, causing a delay when it wakes up after receiving a new request.
  • Vendor Lock-In
    Relying heavily on Heroku’s ecosystem and platform-specific features can lead to vendor lock-in, making it challenging to migrate to another platform if needed.
  • Add-On Costs
    The costs for add-ons can also become significant, as many useful features and integrations require paid add-ons, increasing the overall expense.

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

Heroku videos

What is Heroku | Ask a Dev Episode 14

More videos:

Category Popularity

0-100% (relative to Apache Flink and Heroku)
Big Data
100 100%
0% 0
Cloud Computing
0 0%
100% 100
Stream Processing
100 100%
0% 0
Cloud Hosting
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 Heroku

Apache Flink Reviews

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Heroku Reviews

  1. mark-mercer
    Useful Cloud Platform

    Great service to build, run and manage applications entirely in the cloud!

    🏁 Competitors: Amazon AWS, Dokku on Digital Ocean, Firebase
    👍 Pros:    Easy user interface|Good customer service|Multi-language cloud application platform
    👎 Cons:    Limitation with some addons|Low network performance
  2. jamestelford
    · Full Stack Developer at OutDev ·
    🏁 Competitors: Docker, Amazon AWS
    👍 Pros:    Powerful development environments|Great value for the money|Great customer support|Paas

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Heroku’s focus on simplicity and developer experience makes it a perfect fit for those who want to focus on building their apps, not babysitting servers. Startups and small businesses, in particular, can benefit from Heroku’s ability to accelerate development and deployment, allowing them to get their ideas to market faster.
Source: genezio.com
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Koyeb is a decent alternative to Heroku that you can consider for hosting or deploying your web apps and APIs. It has all the features of Heroku that you will need for your projects. So far, I have not encountered an importer tool for migrating Heroku deployments but I am sure doing that manually will not be that hard. Just like Heroku it offers you an intuitive web UI as...
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Top 10 Netlify Alternatives
Heroku is another alternative to Netlify that doesn’t only host static websites but has the ability to host dynamic websites. This PaaS platform was launched in 2007 and conferred highly scalable features to deploy, host and launch applications.

Social recommendations and mentions

Based on our record, Heroku should be more popular than Apache Flink. It has been mentiond 73 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 / 9 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 / 22 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 / 27 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

Heroku mentions (73)

  • How to deploy your web application? 3 different approaches to consider (+1 bonus)
    Providers include Digital Ocean, Heroku or Render for example. - Source: dev.to / 7 months ago
  • Heroku Reviews Apps prevent delivering bugs on production
    Review Apps run the code in any GitHub PR in a complete, disposable Heroku application. Review Apps each have a unique URL you can share. It’s then super easy for anyone to try the new code. - Source: dev.to / 12 months ago
  • How to keep an HTTP connection alive for 9 hours
    The app is deployed to Heroku and when it came time to switch the mode to email-on-account-creation mode, it was a very simple environment change:. - Source: dev.to / over 1 year ago
  • How to Process Scheduled Queue Jobs in Node.js with BullMQ and Redis on Heroku
    Heroku is a cloud platform that makes it easy to deploy and scale web applications. It provides a number of features that make it ideal for deploying background job applications, including:. - Source: dev.to / almost 2 years ago
  • I made a Bot.. How do I use it?
    Once you've created it you can host it locally (this means leaving the program running on your computer) or host it through a service online. I haven't personally tried this yet, but I believe you can use a site like heroku.com or other similar services. Source: almost 2 years ago
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What are some alternatives?

When comparing Apache Flink and Heroku, 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.

DigitalOcean - Simplifying cloud hosting. Deploy an SSD cloud server in 55 seconds.

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

Linode - We make it simple to develop, deploy, and scale cloud infrastructure at the best price-to-performance ratio in the market.

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

Amazon AWS - Amazon Web Services offers reliable, scalable, and inexpensive cloud computing services. Free to join, pay only for what you use.