Software Alternatives, Accelerators & Startups

Heroku Enterprise VS Apache Airflow

Compare Heroku Enterprise VS Apache Airflow and see what are their differences

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Heroku Enterprise logo Heroku Enterprise

Heroku Enterprise is a flexible IT management for developers that lets them build apps using their preferred languages and tools like Ruby, Java, Python and Node.

Apache Airflow logo Apache Airflow

Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
  • Heroku Enterprise Landing page
    Landing page //
    2023-01-23
  • Apache Airflow Landing page
    Landing page //
    2023-06-17

Heroku Enterprise features and specs

  • Scalability
    Heroku Enterprise offers robust tools for scaling applications easily. You can add more compute resources with just a few clicks, making it simpler to handle traffic spikes and growing user bases.
  • Ease of Use
    Heroku is known for its developer-friendly environment, which simplifies deployment and management of applications. The platform abstracts much of the underlying infrastructure complexity, allowing developers to focus more on coding.
  • Integration
    Heroku Enterprise integrates smoothly with other Salesforce services and third-party tools, providing versatility and extending the capabilities of your applications.
  • Security
    Heroku Enterprise offers enhanced security features such as private spaces, TLS encryption, and compliance with industry standards (e.g., HIPAA, PCI). It ensures that enterprise-level security requirements are met.
  • Support
    Heroku Enterprise clients receive premium support services, including 24/7 customer service, which ensures that any technical issues are resolved quickly and efficiently.

Possible disadvantages of Heroku Enterprise

  • Cost
    Heroku Enterprise can be quite expensive, especially for smaller companies or startups. The pricing structure might be prohibitive for some organizations.
  • Limited Control
    While the ease of use is a strong point, it also means less control over the underlying infrastructure. This can be a drawback for businesses with specific configurations or those requiring deep infrastructure customizations.
  • Performance
    Despite its strong scalability features, some users report that Heroku applications can experience latency issues under heavy load, which might affect performance.
  • Vendor Lock-in
    Relying heavily on Heroku Enterprise for application deployment could pose a risk of vendor lock-in, making it challenging to migrate to other platforms in the future.
  • Customization Limitations
    While Heroku offers numerous add-ons and integrations, it still has limitations in terms of customization compared to managing your own infrastructure, which could be a disadvantage for highly specialized applications.

Apache Airflow features and specs

  • Scalability
    Apache Airflow can scale horizontally, allowing it to handle large volumes of tasks and workflows by distributing the workload across multiple worker nodes.
  • Extensibility
    It supports custom plugins and operators, making it highly customizable to fit various use cases. Users can define their own tasks, sensors, and hooks.
  • Visualization
    Airflow provides an intuitive web interface for monitoring and managing workflows. The interface allows users to visualize DAGs, track task statuses, and debug failures.
  • Flexibility
    Workflows are defined using Python code, which offers a high degree of flexibility and programmatic control over the tasks and their dependencies.
  • Integrations
    Airflow has built-in integrations with a wide range of tools and services such as AWS, Google Cloud, and Apache Hadoop, making it easier to connect to external systems.

Possible disadvantages of Apache Airflow

  • Complexity
    Setting up and configuring Apache Airflow can be complex, particularly for new users. It requires careful management of infrastructure components like databases and web servers.
  • Resource Intensive
    Airflow can be resource-heavy in terms of both memory and CPU usage, especially when dealing with a large number of tasks and DAGs.
  • Learning Curve
    The learning curve can be steep for users who are not familiar with Python or the underlying concepts of workflow management.
  • Limited Real-Time Processing
    Airflow is better suited for batch processing and scheduled tasks rather than real-time event-based processing.
  • Dependency Management
    Managing task dependencies in complex DAGs can become cumbersome and may lead to configuration errors if not properly handled.

Heroku Enterprise videos

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Apache Airflow videos

Airflow Tutorial for Beginners - Full Course in 2 Hours 2022

Category Popularity

0-100% (relative to Heroku Enterprise and Apache Airflow)
Monitoring Tools
100 100%
0% 0
Workflow Automation
0 0%
100% 100
Backup & Restore
100 100%
0% 0
Automation
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 Heroku Enterprise and Apache Airflow

Heroku Enterprise Reviews

We have no reviews of Heroku Enterprise yet.
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Apache Airflow Reviews

5 Airflow Alternatives for Data Orchestration
While Apache Airflow continues to be a popular tool for data orchestration, the alternatives presented here offer a range of features and benefits that may better suit certain projects or team preferences. Whether you prioritize simplicity, code-centric design, or the integration of machine learning workflows, there is likely an alternative that meets your needs. By...
Top 8 Apache Airflow Alternatives in 2024
Apache Airflow is a workflow streamlining solution aiming at accelerating routine procedures. This article provides a detailed description of Apache Airflow as one of the most popular automation solutions. It also presents and compares alternatives to Airflow, their characteristic features, and recommended application areas. Based on that, each business could decide which...
Source: blog.skyvia.com
10 Best Airflow Alternatives for 2024
In a nutshell, you gained a basic understanding of Apache Airflow and its powerful features. On the other hand, you understood some of the limitations and disadvantages of Apache Airflow. Hence, this article helped you explore the best Apache Airflow Alternatives available in the market. So, you can try hands-on on these Airflow Alternatives and select the best according to...
Source: hevodata.com
A List of The 16 Best ETL Tools And Why To Choose Them
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows.
15 Best ETL Tools in 2022 (A Complete Updated List)
Apache Airflow programmatically creates, schedules and monitors workflows. It can also modify the scheduler to run the jobs as and when required.

Social recommendations and mentions

Based on our record, Apache Airflow seems to be more popular. It has been mentiond 75 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 Enterprise mentions (0)

We have not tracked any mentions of Heroku Enterprise yet. Tracking of Heroku Enterprise recommendations started around Mar 2021.

Apache Airflow mentions (75)

  • The DOJ Still Wants Google to Sell Off Chrome
    Is this really true? Something that can be supported by clear evidence? I’ve seen this trotted out many times, but it seems like there are interesting Apache projects: https://airflow.apache.org/ https://iceberg.apache.org/ https://kafka.apache.org/ https://superset.apache.org/. - Source: Hacker News / about 2 months ago
  • 10 Must-Know Open Source Platform Engineering Tools for AI/ML Workflows
    Apache Airflow offers simplicity when it comes to scheduling, authoring, and monitoring ML workflows using Python. The tool's greatest advantage is its compatibility with any system or process you are running. This also eliminates manual intervention and increases team productivity, which aligns with the principles of Platform Engineering tools. - Source: dev.to / 3 months ago
  • Data Orchestration Tool Analysis: Airflow, Dagster, Flyte
    Data orchestration tools are key for managing data pipelines in modern workflows. When it comes to tools, Apache Airflow, Dagster, and Flyte are popular tools serving this need, but they serve different purposes and follow different philosophies. Choosing the right tool for your requirements is essential for scalability and efficiency. In this blog, I will compare Apache Airflow, Dagster, and Flyte, exploring... - Source: dev.to / 3 months ago
  • AIOps, DevOps, MLOps, LLMOps – What’s the Difference?
    Data pipelines: Apache Kafka and Airflow are often used for building data pipelines that can continuously feed data to models in production. - Source: dev.to / 4 months ago
  • Data Engineering with DLT and REST
    This article demonstrates how to work with near real-time and historical data using the dlt package. Whether you need to scale data access across the enterprise or provide historical data for post-event analysis, you can use the same framework to provide customer data. In a future article, I'll demonstrate how to use dlt with a workflow orchestrator such as Apache Airflow or Dagster.``. - Source: dev.to / 5 months ago
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What are some alternatives?

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

ManageEngine RecoveryManager Plus - RecoveryManager Plus is one such enterprise backup solution which has the ability to easily backup and restores both the domain controllers and virtual machines.

Make.com - Tool for workflow automation (Former Integromat)

SECDO - SECDO offers automated endpoint security and incident response solutions

ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.

Traverse Monitoring - Traverse Monitoring is an IT Management software that provides businesses with a network monitoring solution which is capable of handling the tasks of monitoring private clouds, distributed network infestation and virtualized infrastructure.

Microsoft Power Automate - Microsoft Power Automate is an automation platform that integrates DPA, RPA, and process mining. It lets you automate your organization at scale using low-code and AI.