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Astronomer VS Datadog

Compare Astronomer VS Datadog and see what are their differences

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Astronomer logo Astronomer

Capture every user event and route them anywhere. Automatically

Datadog logo Datadog

See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.
  • Astronomer Landing page
    Landing page //
    2023-05-08
  • Datadog Landing page
    Landing page //
    2023-10-05

Datadog is a monitoring and analytics platform for cloud-scale application infrastructure. Combining metrics from servers, databases, and applications, Datadog delivers sophisticated, actionable alerts, and provides real-time visibility of your entire infrastructure. Datadog includes 100+ vendor-supported, prebuilt integrations and monitors hundreds of thousands of hosts.

Astronomer features and specs

  • Managed Airflow
    Astronomer provides a managed service for Apache Airflow, which simplifies the process of deploying, managing, and scaling Airflow instances. This reduces the operational overhead for data engineering teams.
  • Integration and Extensibility
    Astronomer integrates seamlessly with many existing data tools and platforms, allowing organizations to build complex data pipelines and workflows effortlessly. Its flexibility enables users to extend its functionality as needed.
  • User-friendly Interface
    It offers a user-friendly web interface and CLI that makes it easier for teams to develop and monitor their workflows, thereby reducing the learning curve associated with Airflow.
  • Scalability
    Astronomer allows data teams to easily scale their workflows. Users can scale their environments according to need without worrying about infrastructure limitations.
  • Collaboration Features
    With built-in team collaboration features, multiple users can work on data workflows together, thus enhancing productivity and coordination across data projects.

Possible disadvantages of Astronomer

  • Cost
    Using Astronomer can be expensive, particularly when scaling to multiple Airflow instances or when compared to self-managed Airflow options.
  • Dependency on Platform
    Organizations become dependent on Astronomer's platform for managing their Airflow deployments, which can be a concern if there's a need to switch providers or migrate in the future.
  • Customization Limitations
    Though Astronomer is customizable, certain users may find limitations compared to a self-hosted solution where developers have more control over the environment and integrations.
  • Complexity for Small Teams
    For smaller teams with simpler workflows, the complexity and features provided by Astronomer can be overwhelming or unnecessary.

Datadog features and specs

  • Comprehensive Monitoring
    Datadog offers a wide range of monitoring capabilities including infrastructure, application performance, log management, and user experience monitoring. This provides a unified view across the entire tech stack.
  • Integration Ecosystem
    With over 400 integrations available, Datadog can easily connect with virtually any service, application, and technology stack, making it highly versatile.
  • Scalability
    Datadog is designed to scale from small startups to large enterprises, providing functionalities that cater to varied sizes and complexities of operations.
  • Real-Time Data
    The platform provides real-time data and analytics, which is crucial for diagnosing and troubleshooting issues as they arise.
  • Alerting and Notifications
    Advanced alerting and notification features allow users to set up custom alerts based on metrics, enabling proactive problem resolution.
  • User-Friendly Interface
    The user interface is intuitive and easy to navigate, even for those who are not particularly technical, making it accessible to a broader range of users.
  • Security Features
    Datadog includes various security features such as compliance tracking, threat detection, and anomaly detection, enhancing overall security posture.

Possible disadvantages of Datadog

  • Cost
    Datadog can become quite expensive, especially as the volume of monitored data and the number of integrations increases. This can be a limiting factor for smaller businesses.
  • Complexity
    With its extensive feature set, Datadog can be overwhelming for new users, requiring a steep learning curve to master all functionalities.
  • Data Retention
    The default data retention period is often shorter than what some organizations require, leading to additional costs for longer retention.
  • Performance Overhead
    The extensive data collection and monitoring capabilities can add performance overhead to the monitored systems, potentially impacting their performance.
  • Customization Limitations
    While Datadog provides extensive dashboards and visualizations, some users find the customization options to be limited compared to other monitoring solutions.
  • Support
    Some users have reported that the customer support can be slow or insufficient at times, which could be a downside when facing critical issues.

Analysis of Astronomer

Overall verdict

  • Astronomer is a reliable and efficient platform, especially for organizations looking to leverage Apache Airflow without incurring the operational complexity of self-managing the infrastructure. It offers great value by optimizing workflow management and enhancing scalability.

Why this product is good

  • Astronomer (astronomer.io) is considered a good platform for several reasons. It provides a robust solution for managing Apache Airflow, offering features like a scalable and reliable cloud-native platform, easier deployment, and maintenance of workflows. The managed service reduces the overhead of managing infrastructure and allows teams to focus on building and optimizing data pipelines. Additionally, it offers streamlined integration, an intuitive UI, and support for various libraries and frameworks, enhancing the overall development experience for data engineers and scientists.

Recommended for

  • Data engineering teams wanting a managed airflow environment.
  • Organizations requiring scalable and reliable data pipelines.
  • Businesses seeking to minimize infrastructure management overhead associated with Apache Airflow.
  • Data scientists looking for seamless integration with existing data ecosystems.

Analysis of Datadog

Overall verdict

  • Datadog is generally considered a good choice for organizations needing a comprehensive monitoring solution that provides deep insights across various aspects of their technology stack. Its scalability and integration capabilities make it appealing for businesses of all sizes, especially those leveraging cloud services.

Why this product is good

  • Datadog is a powerful monitoring and analytics platform that provides comprehensive visibility into cloud-scale applications. It's known for its robust set of features, including infrastructure monitoring, application performance management, log management, and security monitoring. Datadog's ability to integrate with a vast array of services and technologies makes it a versatile tool for organizations looking to monitor complex systems. Furthermore, its real-time dashboards and alerting capabilities help teams quickly identify and address performance issues, improving reliability and efficiency.

Recommended for

  • Organizations using multiple cloud services and wanting unified monitoring.
  • IT teams looking for a detailed application performance management solution.
  • Businesses that require scalable monitoring for dynamic environments.
  • Companies seeking robust alerting and automation capabilities for infrastructure and application management.

Astronomer videos

+ Add

Astronomer Reviews Sci-Fi Movies, from 'Star Wars' to 'Guardians of the Galaxy' | Vanity Fair

More videos:

  • Review - Real NASA Astronomer Reviews Flat Earth Simulator • Professionals Play

Datadog videos

+ Add

Datadog Review & Walkthrough

More videos:

  • Review - DataDog: What it is and where its going
  • Review - Datadog: 2-Minute Tour

Category Popularity

0-100% (relative to Astronomer and Datadog)

Astronomer

Datadog

Analytics
100 100%
Analytics
0% 0
Monitoring Tools
0 0%
Monitoring Tools
100% 100
Workflow Automation
100 100%
Workflow Automation
0% 0
Log Management
0 0%
Log Management
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 Astronomer and Datadog

Astronomer Reviews

10 Best Airflow Alternatives for 2024
Astronomer acts as a layer for seamless integration with Apache Airflow. Without directly managing the infrastructure of Astronomer you can leverage the capabilities of Apache airflow, ensuring best designs and execution of data pipelines.
Source: hevodata.com

Datadog Reviews

The 10 Best Nagios Alternatives in 2024 (Paid and Open-source)
10 Best Datadog Alternatives to Consider in 2023 Datadog is one of the most potent and versatile players on the market, but they have their fair share of downsides. The monitoring and observability space is quite competitive, so we will discuss 10 of the best Datadog alternatives and compare their pros and cons to determine which is better suited for your needs.
Source: betterstack.com
Top 10 Grafana Alternatives in 2024
While all Grafana alternatives do not offer pricing transparency, go for a flexible pricing structure that fits your budget. Tools like Datadog offer pricing based on data volume or monitoring scope, while Middleware offers a flexible pay-as-you-go pricing structure.
Source: middleware.io
Top 11 Grafana Alternatives & Competitors [2024]
Open Source vs. Proprietary: Determine whether an open-source solution like SigNoz or a proprietary one like Datadog better aligns with your requirements and budget. Open-source tools often offer more customization and community support, while proprietary tools may provide more comprehensive out-of-the-box features and dedicated customer service. At SigNoz, we offer both...
Source: signoz.io
10 Best Grafana Alternatives [2023 Comparison]
Datadog is a massive tool that offers a lot of features and solutions, including log management. But before we dive too deep, please note that Datadog is expensive. It absolutely is not for anyone other than large-budgeted corporations. Just take a look at what people are saying on X.
Source: sematext.com
5 Best DevSecOps Tools in 2023
There are many platforms that can be utilized for monitoring and alerting. Some examples are New Relic, Datadog, AWS CloudWatch, Sentry, Dynatrace, and others. Again, these providers each have pros and cons related to pricing, offering, ad vendor lock-in. So research the options to see what may possibly be best for a given situation.
Source: devopsauthority.tech

Social recommendations and mentions

Datadog might be a bit more popular than Astronomer. We know about 5 links to it since March 2021 and only 4 links to Astronomer. 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.

Astronomer mentions (4)

  • I’ve just got a data engineering from BI developer role by transferring internally and I’m struggling
    A quick tip for airflow if you don't have a local install (and I heartily recommend a local install - astronomer.io has an easy to set up container). Source: over 2 years ago
  • Farnance: How Julian built a SaaS for farmers with Wasp and won a hackathon!
    Julian LaNeve is an engineer and data scientist who currently works at Astronomer.io as a Product Manager. In his free time, he enjoys playing poker, chess and winning data science competitions. - Source: dev.to / over 2 years ago
  • I am looking for a roadmap on getting into Data Engineering. I can't hope to follow the popular roadmap shared on this sub.
    Then load up docker, don't need to be a docker expert, just install docker desktop on windows or use linux. Go to astronomer.io and look at how to run airflow (cron++) in docker. Get that working. If you don't know python but do program in some language, you should be able to get up to speed on the basics pretty quickly. If you know python, it will be a breeze. Source: over 3 years ago
  • Finding the right workflow orchestration tool
    Hello guys, I am currently looking for the right orchestration to build a data pipeline composed of long running tasks (python scripts) among which some run in parallel. Although I was firstly hesitating between Apache Airflow and AWS Step functions, it appeared setting Airflow for production might be too complicated without using a way too expensive service meant for that intent( aws managed worflows or... Source: about 4 years ago

Datadog mentions (5)

  • Send the logs of your Shuttle-powered backend to Datadog
    Ideally, if we had access to the underlying infrastructure, we could probably install the Datadog Agent and configure it to send our logs directly to Datadog, or even use AWS Lambda functions or Azure Event Hub + Azure Functions in case we were facing some specific cloud scenarios. - Source: dev.to / over 1 year ago
  • I wanted a self hosted alternative to Atlassian status page so I build my own application !
    Currently supported : Datadog, Jenkins, DNS, HTTP. Source: over 2 years ago
  • Datadog on Kubernetes: Avoiding Common Pitfalls
    Datadog is a powerful monitoring and security platform that gives you visibility into end-to-end traces, application metrics, logs, and infrastructure. While Datadog has great documentation on their Kubernetes integration, we've observed that there's some missed nuance that leads to common pitfalls. - Source: dev.to / almost 4 years ago
  • Post-DockerCon spam
    .. Is to see you email address being silently distributed to every single company that I've watched a talk from. And now suddenly get several promotional spam emails per day from some 4-5 different domains like instana.com, datadoghq.com, snyk.io, cockroachlabs.com (some of them send even multiple emails per day!). Source: almost 4 years ago
  • Never write a UserService again
    We're commonly doing this with logging, using services such as Loggly or DataDog. We're using managed databases, be it on AWS, Heroku or database-vendor-specific solutions. We're storing binaries on S3. Externalising user authentication and authorization might be a good candidate as well. - Source: dev.to / about 4 years ago

What are some alternatives?

When comparing Astronomer and Datadog, you can also consider the following products

Kestra.io - Infinitely scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code.

Zabbix - Track, record, alert and visualize performance and availability of IT resources

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

Dynatrace - Cloud-based quality testing, performance monitoring and analytics for mobile apps and websites. Get started with Keynote today!

Dagster - The cloud-native open source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability.

NewRelic - New Relic is a Software Analytics company that makes sense of billions of metrics across millions of apps. We help the people who build modern software understand the stories their data is trying to tell them.

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