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Heroku VS Apache Storm

Compare Heroku VS Apache Storm and see what are their differences

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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 Storm logo Apache Storm

Apache Storm is a free and open source distributed realtime computation system.
  • Heroku Landing page
    Landing page //
    2023-10-05
  • Apache Storm Landing page
    Landing page //
    2019-03-11

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 Storm features and specs

  • Real-Time Processing
    Apache Storm is designed for processing data in real-time, which makes it ideal for applications like fraud detection, recommendation systems, and monitoring tools.
  • Scalability
    Storm is capable of scaling horizontally, allowing it to handle increasing amounts of data by adding more nodes, making it suitable for large-scale applications.
  • Fault Tolerance
    Storm provides robust fault-tolerance mechanisms by rerouting tasks from failed nodes to operational ones, ensuring continuous processing.
  • Broad Language Support
    Apache Storm supports multiple programming languages, including Java, Python, and Ruby, allowing developers to use the language they are most comfortable with.
  • Open Source Community
    Being an Apache project, Storm benefits from a strong open-source community, which contributes to its development and offers abundant resources and support.

Possible disadvantages of Apache Storm

  • Complex Setup
    Setting up and configuring Apache Storm can be complex and time-consuming, requiring detailed knowledge of its architecture and the underlying infrastructure.
  • High Learning Curve
    The architecture and components of Storm can be difficult for new users to grasp, leading to a steeper learning curve compared to some other streaming platforms.
  • Maintenance Overhead
    Managing and maintaining a Storm cluster can require significant effort, including monitoring, troubleshooting, and scaling the infrastructure.
  • Error Handling
    While Storm is fault-tolerant, its error handling at the application level can sometimes be challenging, requiring careful design to manage failures effectively.
  • Resource Intensive
    Storm can be resource-intensive, particularly in terms of memory and CPU usage, which can lead to increased costs and necessitate powerful hardware.

Heroku videos

+ Add

What is Heroku | Ask a Dev Episode 14

More videos:

Apache Storm videos

+ Add

Apache Storm Tutorial For Beginners | Apache Storm Training | Apache Storm Example | Edureka

More videos:

  • Review - Developing Java Streaming Applications with Apache Storm
  • Review - Atom Text Editor Option - Real-Time Analytics with Apache Storm

Category Popularity

0-100% (relative to Heroku and Apache Storm)

Heroku

Apache Storm

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

User comments

Share your experience with using Heroku and Apache Storm. 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 Heroku and Apache Storm

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
10 Top Firebase Alternatives to Ignite Your Development in 2024
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
2023 Firebase Alternatives: Top 10 Open-Source & Free
Heroku Postgres – Majority of businesses like Heroku because of its SQL database support. Yes, PostgreSQL as a service is an appealing product of this PaaS vendor with quick deployment approaches.
Source: digitalcruch.com
5 Free Heroku Alternatives with Free Plan for Developers
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...
Source: www.ilovefreesoftware.com
Choosing the best Next.js hosting platform
However, there are a few disadvantages to Heroku. First of all, despite its build pack, Heroku will run your project as a Node.js application. As a result, you will lose some of Next.js’ most interesting features, such as Incremental Static Regeneration. Analytics are replaced by metrics and measured throughput, response time, and memory usage (only on paid plans).
Source: blog.logrocket.com
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.
Source: blog.back4app.com

Apache Storm Reviews

Top 15 Kafka Alternatives Popular In 2021
Apache Storm is a recognized, distributed, open-source real-time computational system. It is free, simple to use, and helps in easily and accurately processing multiple data streams in real-time. Because of its simplicity, it can be utilized with any programming language and that is one reason it is a developer’s preferred choice. It is fast, scalable, and integrates well...
Source: www.spec-india.com
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Storm is an open-source distributed real-time computational system for processing data streams. Similar to what Hadoop does for batch processing, Apache Storm does for unbounded streams of data in a reliable manner. Built by Twitter, Apache Storm specifically aims at the transformation of data streams. Storm has many use cases like real-time analytics, online machine...
Source: www.analyticsinsight.net

Social recommendations and mentions

Based on our record, Heroku should be more popular than Apache Storm. 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.

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
View more

Apache Storm mentions (11)

  • Data Engineering and DataOps: A Beginner's Guide to Building Data Solutions and Solving Real-World Challenges
    There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 2 years ago
  • Real Time Data Infra Stack
    Although this article lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem. - Source: dev.to / over 2 years ago
  • In One Minute : Hadoop
    Storm, a system for real-time and stream processing. - Source: dev.to / over 2 years ago
  • Elon Musk reportedly wants to fire 75% of Twitter’s employees
    Google has scaled well and has helped others scale, Twitter has always been behind by years. I think the only thing they did well was Twitter Storm, now taken up by Apache Foundation. Source: over 2 years ago
  • Spark for beginners - and you
    Streaming: Sparks Streamings's latency is at least 500ms, since it operates on micro-batches of records, instead of processing one record at a time. Native streaming tools like Storm, Apex or Flink might be better for low-latency applications. - Source: dev.to / over 3 years ago
View more

What are some alternatives?

When comparing Heroku and Apache Storm, you can also consider the following products

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

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

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

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

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

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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