Datadog vs Honeybadger

Overview

Honeybadger

Stacks156

Followers112

Votes44

Datadog

Stacks9.8K

Followers8.2K

Votes861

Datadog vs Honeybadger: What are the differences?

Introduction

Cost: Datadog and Honeybadger have different pricing models. Datadog offers a variety of plans based on the number of hosts and the features required, while Honeybadger has a fixed monthly cost regardless of the number of hosts or features used.
Monitoring Capabilities: Datadog provides a comprehensive monitoring solution that covers a wide range of technologies and services, including infrastructure, applications, logs, and more. On the other hand, Honeybadger focuses mainly on error monitoring and exception handling for web applications.
Alerting and Notification: Datadog offers flexible alerting options with customizable thresholds, notifications, and integrations with popular communication channels like Slack. Honeybadger also provides alerting capabilities but is more focused on sending notifications via email or third-party messaging services.
Integration Ecosystem: Datadog has an extensive integration ecosystem, allowing users to integrate with various third-party tools and services, such as AWS, Docker, Kubernetes, and more. Honeybadger, while it does offer integrations with popular tools like GitHub and GitLab, has a more limited integration ecosystem compared to Datadog.
Data Retention: Datadog offers longer data retention periods for monitoring data, allowing users to store and analyze historical data for a longer period. Honeybadger, on the other hand, has shorter data retention periods, limiting the amount of historical data that can be accessed and analyzed.
User Interface: Datadog provides a highly customizable and visually appealing user interface, with advanced data visualization capabilities and user-friendly dashboards. Honeybadger also offers a user-friendly interface, but it is more focused on simplicity and ease of use, with fewer customization options compared to Datadog.

In Summary, Datadog and Honeybadger differ in terms of cost, monitoring capabilities, alerting and notification options, integration ecosystem, data retention periods, and user interface.

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Advice on Honeybadger, Datadog

Farzeem Diamond

Software Engineer at IVP

Jul 21, 2020

Needs adviceon

Datadog

Dynatrace

AppDynamics

Hey there! We are looking at Datadog, Dynatrace, AppDynamics, and New Relic as options for our web application monitoring.

Current Environment: .NET Core Web app hosted on Microsoft IIS

Future Environment: Web app will be hosted on Microsoft Azure

Tech Stacks: IIS, RabbitMQ, Redis, Microsoft SQL Server

Requirement: Infra Monitoring, APM, Real - User Monitoring (User activity monitoring i.e., time spent on a page, most active page, etc.), Service Tracing, Root Cause Analysis, and Centralized Log Management.

Please advise on the above. Thanks!

1.59M views1.59M

Comments

Medeti

Jun 27, 2020

Needs adviceon

Amazon EKS

Kubernetes

AWS Elastic Load Balancing (ELB)

We are looking for a centralised monitoring solution for our application deployed on Amazon EKS. We would like to monitor using metrics from Kubernetes, AWS services (NeptuneDB, AWS Elastic Load Balancing (ELB), Amazon EBS, Amazon S3, etc) and application microservice's custom metrics.

We are expected to use around 80 microservices (not replicas). I think a total of 200-250 microservices will be there in the system with 10-12 slave nodes.

We tried Prometheus but it looks like maintenance is a big issue. We need to manage scaling, maintaining the storage, and dealing with multiple exporters and Grafana. I felt this itself needs few dedicated resources (at least 2-3 people) to manage. Not sure if I am thinking in the correct direction. Please confirm.

You mentioned Datadog and Sysdig charges per host. Does it charge per slave node?

1.51M views1.51M

Comments

Benoit

Principal Engineer at Sqreen

Sep 17, 2019

Decided

I chose Datadog APM because the much better APM insights it provides (flamegraph, percentiles by default).

The drawbacks of this decision are we had to move our production monitoring to TimescaleDB + Telegraf instead of NR Insight

NewRelic is definitely easier when starting out. Agent is only a lib and doesn't require a daemon

457k views457k

Comments

Detailed Comparison

Honeybadger	Datadog
Honeybadger does more than report errors, it helps you work with your team to fix them. Errors can be assigned. You can comment via email. And a fine-grained permissions system means you control who has access to each specific project.	Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog!
Collaboration tools for your team;A blazing-fast error drill-down UI;Tons of notification options;Full text exception search;Simple pricing and great support;Github, Campfire, Hipchat, Pivotal, and more;SMS alerts;Syntax Highlighting;Keyboard Navigation	14-day Free Trial for an unlimited number of hosts;200+ turn-key integrations for data aggregation;Clean graphs of StatsD and other integrations;Slice and dice graphs and alerts by tags, roles, and more;Easy-to-use search for hosts, metrics, and tags;Alert notifications via e-mail and PagerDuty;Receive alerts on any metric, for a single host or an entire cluster;Full API access in more than 15 languages;Overlay metrics and events across disparate sources;Out-of-the-box and customizable monitoring dashboards;Easy way to compute rates, ratios, averages, or integrals;Sampling intervals of 10 seconds;Mute all alerts with 1 click during upgrades and maintenance;Tools for team collaboration
Statistics
Stacks 156	Stacks 9.8K
Followers 112	Followers 8.2K
Votes 44	Votes 861
Pros & Cons
Pros 9 Easy setup 9 Rails integration 5 Github integration 4 Javascript integration 4 Slack Integration	Pros 140 Monitoring for many apps (databases, web servers, etc) 107 Easy setup 87 Powerful ui 84 Powerful integrations 70 Great value Cons 20 Expensive 4 No errors exception tracking 2 External Network Goes Down You Wont Be Logging 1 Complicated
Integrations
Bitbucket Intercom Forge GitLab Flowdock ClickUp Google Hangouts Chat Microsoft Teams Linear Slack	NGINX Google App Engine Apache HTTP Server Java Docker Pingdom MySQL Ruby Python Memcached

What are some alternatives to Honeybadger, Datadog?

New Relic

The world’s best software and DevOps teams rely on New Relic to move faster, make better decisions and create best-in-class digital experiences. If you run software, you need to run New Relic. More than 50% of the Fortune 100 do too.

Sentry

Sentry’s Application Monitoring platform helps developers see performance issues, fix errors faster, and optimize their code health.

Rollbar

Rollbar is the leading continuous code improvement platform that proactively discovers, predicts, and remediates errors with real-time AI-assisted workflows. With Rollbar, developers continually improve their code and constantly innovate ra

Bugsnag

Bugsnag captures errors from your web, mobile and back-end applications, providing instant visibility into user impact. Diagnostic data and tools are included to help your team prioritize, debug and fix exceptions fast.

Raygun

Raygun gives you a window into how users are really experiencing your software applications. Detect, diagnose and resolve issues that are affecting end users with greater speed and accuracy.

Opbeat

Opbeat is application monitoring for developers, and gives you performance metrics, error logging, release tracking and workflow in one smart product.

Airbrake

Airbrake collects errors for your applications in all major languages and frameworks. We alert you to new errors and give you critical context, trends and details needed to find and fix errors fast.

AppSignal

AppSignal gives you and your team alerts and detailed metrics about your Ruby, Node.js or Elixir application. Sensible pricing, no aggressive sales & support by developers.

AppDynamics

AppDynamics develops application performance management (APM) solutions that deliver problem resolution for highly distributed applications through transaction flow monitoring and deep diagnostics.

Stackify

Stackify offers the only developers-friendly innovative cloud based solution that fully integrates application performance management (APM) with error and log. Allowing them to easily monitor, detect and resolve application issues faster

Related Comparisons

Datadog vs Honeybadger: What are the differences?

Introduction

Cost: Datadog and Honeybadger have different pricing models. Datadog offers a variety of plans based on the number of hosts and the features required, while Honeybadger has a fixed monthly cost regardless of the number of hosts or features used.
Monitoring Capabilities: Datadog provides a comprehensive monitoring solution that covers a wide range of technologies and services, including infrastructure, applications, logs, and more. On the other hand, Honeybadger focuses mainly on error monitoring and exception handling for web applications.
Alerting and Notification: Datadog offers flexible alerting options with customizable thresholds, notifications, and integrations with popular communication channels like Slack. Honeybadger also provides alerting capabilities but is more focused on sending notifications via email or third-party messaging services.
Integration Ecosystem: Datadog has an extensive integration ecosystem, allowing users to integrate with various third-party tools and services, such as AWS, Docker, Kubernetes, and more. Honeybadger, while it does offer integrations with popular tools like GitHub and GitLab, has a more limited integration ecosystem compared to Datadog.
Data Retention: Datadog offers longer data retention periods for monitoring data, allowing users to store and analyze historical data for a longer period. Honeybadger, on the other hand, has shorter data retention periods, limiting the amount of historical data that can be accessed and analyzed.
User Interface: Datadog provides a highly customizable and visually appealing user interface, with advanced data visualization capabilities and user-friendly dashboards. Honeybadger also offers a user-friendly interface, but it is more focused on simplicity and ease of use, with fewer customization options compared to Datadog.

In Summary, Datadog and Honeybadger differ in terms of cost, monitoring capabilities, alerting and notification options, integration ecosystem, data retention periods, and user interface.

Datadog vs Honeybadger

Overview

Datadog vs Honeybadger: What are the differences?