Datadog vs Honeycomb vs New Relic

Overview

New Relic

Stacks22.7K

Followers8.7K

Votes1.9K

Datadog

Stacks9.8K

Followers8.2K

Votes861

Honeycomb

Stacks80

Followers112

Votes8

Datadog vs Honeycomb vs New Relic: What are the differences?

Introduction:

When evaluating monitoring tools for your organization, it is crucial to understand the key differences between Datadog, Honeycomb, and New Relic. Each of these tools offers unique features and functionalities that cater to different monitoring needs.

Data Collection and Observability Approach: Datadog focuses on collecting a wide range of metrics, logs, and traces to provide a comprehensive view of the system's performance. Honeycomb, on the other hand, adopts an observability-driven approach, emphasizing the ability to ask ad-hoc questions and explore data in real-time to gain deeper insights. New Relic combines both approaches by offering a platform that captures metrics, traces, and logs while also enabling users to perform ad-hoc queries for deeper analysis.
Customizability and Flexibility: Datadog provides a robust set of pre-built integrations and dashboards, making it easy to get started with monitoring. Honeycomb offers a high level of customizability, allowing users to define their own events and attributes for analysis. New Relic strikes a balance by providing out-of-the-box solutions while offering customization options for advanced users.
Cost and Pricing Structure: Datadog has a straightforward pricing model based on the volume of data ingested and the features included. Honeycomb's pricing is based on the number of events ingested and the retention period, with options for bursts of high activity. New Relic offers tiered pricing based on features and the level of support required, making it suitable for organizations of all sizes.
Querying and Analysis Capabilities: Datadog provides powerful querying and analysis tools that allow users to create complex dashboards and alerts based on aggregated data. Honeycomb's strength lies in its query language and visualization capabilities, enabling users to uncover patterns and anomalies in real-time. New Relic offers a user-friendly interface for querying data and a variety of visualization options for analyzing performance metrics.
Community and Ecosystem: Datadog boasts a large community of users and a marketplace where users can share integrations and dashboards. Honeycomb has a strong focus on building a community around observability practices and sharing insights through blogs and events. New Relic has a thriving community forum and extensive documentation to support users in implementing monitoring best practices.

In Summary, understanding the key differences between Datadog, Honeycomb, and New Relic can help organizations choose the monitoring tool that best fits their specific needs and requirements.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Advice on New Relic, Datadog, Honeycomb

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

New Relic	Datadog	Honeycomb
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.	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!	We built Honeycomb to answer the hard questions that come up when you're trying to operate your software–to debug microservices, serverless, distributed systems, polyglot persistence, containers, and a world of fast, parallel deploys.
Performance Data Retention;Real-User Response Time, Throughput, & Breakdown by Layer;App Response Time, Throughput, & Breakdown by Component;App Availability Monitoring, Alerting, and Notification;Automatic Application Topology Mapping;Server Resource and Availability Monitoring;Error Detection, Alerting, & Analysis;JVM Performance Analyzer;Database Call Response Time & Throughput;Performance Data API Access;Code Level Diagnostics, Transaction Tracing, & Stack Trace Details;Slow SQL and SQL Performance Details;Real-User Breakdown by Web Page, Browser, & Geography;Track Individual Key Transactions;Mobile Features- Alerting, Summary Data, Overview Page, Topo Map, HTTP Requests, HTTP Error Summary, HTTP Error Detail, Versions, Carriers, Devices, Geo Map	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	High-performance querying against high-cardinality or sparse events.; Accepts any structured JSON objects with a write key.; Submit events via API.; Open source agents, log tailers, SDKs, and integrations.; Customizable high-performance query windows.; Customizable storage windows provide control over retention and costs.; Always have access to the the raw data behind query results and graphs.; Shared boards.; Individual and team query histories.; Triggers and notifications.; Secure Tenancy for data compliance.
Statistics
Stacks 22.7K	Stacks 9.8K	Stacks 80
Followers 8.7K	Followers 8.2K	Followers 112
Votes 1.9K	Votes 861	Votes 8
Pros & Cons
Pros 414 Easy setup 344 Really powerful 245 Awesome visualization 194 Ease of use 151 Great ui Cons 20 Pricing model doesn't suit microservices 10 UI isn't great 7 Visualizations aren't very helpful 7 Expensive 5 Hard to understand why things in your app are breaking	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	Pros 3 BubbleUp + Heat maps 2 Powerful UI 2 High-Cardinality Data 1 Better Value
Integrations
No integrations available	NGINX Google App Engine Apache HTTP Server Java Docker Pingdom MySQL Ruby Python Memcached	JavaScript Ruby ExpressJS Slack NGINX PostgreSQL MySQL Python Golang AWS Elastic Load Balancing (ELB)

What are some alternatives to New Relic, Datadog, Honeycomb?

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.

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

Skylight

Skylight is a smart profiler for your Rails apps that visualizes request performance across all of your servers.

Librato

Librato provides a complete solution for monitoring and understanding the metrics that impact your business at all levels of the stack. We provide everything you need to visualize, analyze, and actively alert on the metrics that matter to you.

Keymetrics

PM2 is a production process manager for Node.js applications with a built-in load balancer. It allows you to keep applications alive forever, to reload them without downtime and to facilitate common system admin tasks.

Dynatrace

It is an AI-powered, full stack, automated performance management solution. It provides user experience analysis that identifies and resolves application performance issues faster than ever before.

SignalFx

We provide operational intelligence for today’s elastic architectures through monitoring specifically designed for microservices and containers with: -powerful and proactive alerting -metrics aggregation -visualization into time series data

Scout

Scout APM helps developers quickly pinpoint & resolve performance issues before the customer ever sees them. Spend less time debugging & more time building with a streamlined interface & tracing logic that ties bottlenecks to source code.

Related Comparisons

Datadog vs Honeycomb vs New Relic: What are the differences?

Introduction:

Data Collection and Observability Approach: Datadog focuses on collecting a wide range of metrics, logs, and traces to provide a comprehensive view of the system's performance. Honeycomb, on the other hand, adopts an observability-driven approach, emphasizing the ability to ask ad-hoc questions and explore data in real-time to gain deeper insights. New Relic combines both approaches by offering a platform that captures metrics, traces, and logs while also enabling users to perform ad-hoc queries for deeper analysis.
Customizability and Flexibility: Datadog provides a robust set of pre-built integrations and dashboards, making it easy to get started with monitoring. Honeycomb offers a high level of customizability, allowing users to define their own events and attributes for analysis. New Relic strikes a balance by providing out-of-the-box solutions while offering customization options for advanced users.
Cost and Pricing Structure: Datadog has a straightforward pricing model based on the volume of data ingested and the features included. Honeycomb's pricing is based on the number of events ingested and the retention period, with options for bursts of high activity. New Relic offers tiered pricing based on features and the level of support required, making it suitable for organizations of all sizes.
Querying and Analysis Capabilities: Datadog provides powerful querying and analysis tools that allow users to create complex dashboards and alerts based on aggregated data. Honeycomb's strength lies in its query language and visualization capabilities, enabling users to uncover patterns and anomalies in real-time. New Relic offers a user-friendly interface for querying data and a variety of visualization options for analyzing performance metrics.
Community and Ecosystem: Datadog boasts a large community of users and a marketplace where users can share integrations and dashboards. Honeycomb has a strong focus on building a community around observability practices and sharing insights through blogs and events. New Relic has a thriving community forum and extensive documentation to support users in implementing monitoring best practices.

In Summary, understanding the key differences between Datadog, Honeycomb, and New Relic can help organizations choose the monitoring tool that best fits their specific needs and requirements.

Datadog vs Honeycomb vs New Relic

Overview