Datadog vs Kibana vs New Relic

Overview

New Relic

Stacks22.7K

Followers8.7K

Votes1.9K

Datadog

Stacks9.8K

Followers8.2K

Votes861

Kibana

Stacks20.6K

Followers16.4K

Votes262

GitHub Stars20.8K

Forks8.5K

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

Datadog and Kibana are popular monitoring and analytics platforms, whereas New Relic is a performance monitoring tool. Each of these tools offers unique features and capabilities to help businesses monitor and optimize their applications. Below are key differences between Datadog, Kibana, and New Relic.

1. **Functionality**: Datadog is known for its extensive monitoring capabilities, including infrastructure monitoring, application performance monitoring, log management, and more. Kibana, on the other hand, is more focused on data visualization and analysis, particularly for Elasticsearch data. New Relic specializes in application performance monitoring, providing real-time insights into the health and performance of software applications.

2. **Integration**: Datadog offers a wide range of integrations with various third-party tools and services, making it easy to collect and analyze data from different sources. Kibana is typically used in conjunction with Elasticsearch, providing powerful search and visualization capabilities for Elasticsearch data. New Relic also offers integrations with popular development and monitoring tools to streamline the monitoring and optimization process.

3. **User Interface**: Datadog features a user-friendly and intuitive dashboard that allows users to monitor their infrastructure, applications, and logs with ease. Kibana's strength lies in its visualization tools, offering a customizable interface for exploring and analyzing data stored in Elasticsearch. New Relic provides a clean and organized user interface that gives users a comprehensive view of the performance of their applications.

4. **Alerting**: Datadog offers robust alerting capabilities, allowing users to set up custom alerts based on predefined conditions to proactively monitor their systems. Kibana's alerting features are more limited compared to Datadog, focusing primarily on alerting based on specific data thresholds. New Relic provides flexible alerting options to notify users of any deviations from the expected performance metrics.

5. **Scalability**: Datadog is highly scalable and can handle large volumes of data, making it suitable for organizations of all sizes. Kibana's scalability depends on the underlying Elasticsearch cluster, with larger clusters required for handling increased data volume. New Relic offers scalable monitoring solutions that can adapt to the growth and changing needs of businesses.

6. **Cost**: Datadog's pricing is based on the volume of data ingested and the features included, making it a customizable option for businesses with varying monitoring needs. Kibana is open-source and free to use, but additional functionalities may require a subscription to Elasticsearch. New Relic's pricing is based on the number of monitored hosts or user licenses, offering different tiers to accommodate different business sizes.

In Summary, Datadog, Kibana, and New Relic each offer unique functionalities and strengths in monitoring and analytics, catering to different business requirements and preferences.

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Advice on New Relic, Datadog, Kibana

Leonardo Henrique da

Pleno QA Enginneer at SolarMarket

Dec 8, 2020

Decided

The objective of this work was to develop a system to monitor the materials of a production line using IoT technology. Currently, the process of monitoring and replacing parts depends on manual services. For this, load cells, microcontroller, Broker MQTT, Telegraf, InfluxDB, and Grafana were used. It was implemented in a workflow that had the function of collecting sensor data, storing it in a database, and visualizing it in the form of weight and quantity. With these developed solutions, he hopes to contribute to the logistics area, in the replacement and control of materials.

403k views403k

Comments

matteo1989it

Jun 26, 2019

Reviewon

Kibana

Grafana

Elasticsearch

I use both Kibana and Grafana on my workplace: Kibana for logging and Grafana for monitoring. Since you already work with Elasticsearch, I think Kibana is the safest choice in terms of ease of use and variety of messages it can manage, while Grafana has still (in my opinion) a strong link to metrics

757k views757k

Comments

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

Detailed Comparison

New Relic	Datadog	Kibana
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!	Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.
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	Flexible analytics and visualization platform;Real-time summary and charting of streaming data;Intuitive interface for a variety of users;Instant sharing and embedding of dashboards
Statistics
GitHub Stars -	GitHub Stars -	GitHub Stars 20.8K
GitHub Forks -	GitHub Forks -	GitHub Forks 8.5K
Stacks 22.7K	Stacks 9.8K	Stacks 20.6K
Followers 8.7K	Followers 8.2K	Followers 16.4K
Votes 1.9K	Votes 861	Votes 262
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 Expensive 7 Visualizations aren't very helpful 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 88 Easy to setup 65 Free 45 Can search text 21 Has pie chart 13 X-axis is not restricted to timestamp Cons 7 Unintuituve 4 Works on top of elastic only 4 Elasticsearch is huge 3 Hardweight UI
Integrations
AppHarbor Cloudability HP Cloud Compute cloudControl Papertrail Loggly Ducksboard Blitz Pivotal Tracker Red Hat OpenShift	NGINX Google App Engine Apache HTTP Server Java Docker Pingdom MySQL Ruby Python Memcached	Logstash Elasticsearch Beats

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

Grafana

Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.

Prometheus

Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.

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.

Nagios

Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.

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.

Netdata

Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all of your physical & virtual servers, cloud deployments, Kubernetes clusters & edge/IoT devices, to monitor systems, containers & apps

AppDynamics

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

Zabbix

Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.

Sensu

Sensu is the future-proof solution for multi-cloud monitoring at scale. The Sensu monitoring event pipeline empowers businesses to automate their monitoring workflows and gain deep visibility into their multi-cloud environments.

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 Kibana vs New Relic: What are the differences?

Datadog and Kibana are popular monitoring and analytics platforms, whereas New Relic is a performance monitoring tool. Each of these tools offers unique features and capabilities to help businesses monitor and optimize their applications. Below are key differences between Datadog, Kibana, and New Relic.

1. **Functionality**: Datadog is known for its extensive monitoring capabilities, including infrastructure monitoring, application performance monitoring, log management, and more. Kibana, on the other hand, is more focused on data visualization and analysis, particularly for Elasticsearch data. New Relic specializes in application performance monitoring, providing real-time insights into the health and performance of software applications.

2. **Integration**: Datadog offers a wide range of integrations with various third-party tools and services, making it easy to collect and analyze data from different sources. Kibana is typically used in conjunction with Elasticsearch, providing powerful search and visualization capabilities for Elasticsearch data. New Relic also offers integrations with popular development and monitoring tools to streamline the monitoring and optimization process.

3. **User Interface**: Datadog features a user-friendly and intuitive dashboard that allows users to monitor their infrastructure, applications, and logs with ease. Kibana's strength lies in its visualization tools, offering a customizable interface for exploring and analyzing data stored in Elasticsearch. New Relic provides a clean and organized user interface that gives users a comprehensive view of the performance of their applications.

4. **Alerting**: Datadog offers robust alerting capabilities, allowing users to set up custom alerts based on predefined conditions to proactively monitor their systems. Kibana's alerting features are more limited compared to Datadog, focusing primarily on alerting based on specific data thresholds. New Relic provides flexible alerting options to notify users of any deviations from the expected performance metrics.

5. **Scalability**: Datadog is highly scalable and can handle large volumes of data, making it suitable for organizations of all sizes. Kibana's scalability depends on the underlying Elasticsearch cluster, with larger clusters required for handling increased data volume. New Relic offers scalable monitoring solutions that can adapt to the growth and changing needs of businesses.

6. **Cost**: Datadog's pricing is based on the volume of data ingested and the features included, making it a customizable option for businesses with varying monitoring needs. Kibana is open-source and free to use, but additional functionalities may require a subscription to Elasticsearch. New Relic's pricing is based on the number of monitored hosts or user licenses, offering different tiers to accommodate different business sizes.

In Summary, Datadog, Kibana, and New Relic each offer unique functionalities and strengths in monitoring and analytics, catering to different business requirements and preferences.

Datadog vs Kibana vs New Relic

Overview