New Relic vs Datadog vs SignalFx | What are the differences? | StackShare

Datadog vs New Relic vs SignalFx

Overview

New Relic

Stacks21.0K

Followers8.7K

Votes1.9K

Datadog

Stacks9.6K

Followers8.2K

Votes861

SignalFx

Stacks53

Followers110

Votes22

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

Key Differences between Datadog, New Relic, and SignalFx

Data Collection Methods: Datadog primarily collects data through agents deployed on servers, whereas New Relic uses agents or SDKs within the application code, and SignalFx relies on a combination of agents and integrations with other tools.
Monitoring Capabilities: Datadog offers comprehensive monitoring for infrastructure, applications, logs, and user experience, whereas New Relic focuses more on application performance monitoring, and SignalFx specializes in real-time analytics and monitoring for cloud infrastructure.
Alerting and Notification Features: Datadog provides customizable alerts and flexible notification options, New Relic offers alerting based on various metrics and thresholds, and SignalFx has robust alerting capabilities with support for anomaly detection and forecasting.
Scalability and Flexibility: Datadog is known for its scalability and flexibility in handling large amounts of data and diverse environments, New Relic is popular for its ease of use and simplicity, and SignalFx is preferred for its ability to scale with dynamic cloud-based architectures.
Cost and Pricing Model: Datadog offers a usage-based pricing model with different plans for infrastructure monitoring, APM, and log management, New Relic has a subscription-based pricing structure based on the number of host instances or application instances, and SignalFx offers a consumption-based pricing model with charges for ingested data and additional features.
Integration Ecosystem: Datadog has a wide range of integrations with popular tools and services, New Relic also provides integrations for various platforms and technologies, and SignalFx specializes in integrations with cloud-native services and container orchestration platforms.

In Summary, Datadog, New Relic, and SignalFx offer unique monitoring solutions tailored to different needs with varying strengths in data collection methods, monitoring capabilities, alerting features, scalability, pricing models, and integration ecosystems.

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Advice on New Relic, Datadog, SignalFx

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	SignalFx
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 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
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	Beautiful streaming visualizations; Meaningful, fast alerting using SignalFlow analytics; High resolution metrics up to 1 sec; Filter & aggregate by dimesions like source, geo, customer, etc; Build custom real-time analytics pipelines; Use dynamic alert thresholds like moving averages; Get alerts in PagerDuty, VictorOps, HipChat, Slack, & more; Overlay events like alerts, pushes, CI runs, etc; Integrations with AWS services, Docker, Mesos, Kubernetes, Kafka, Cassandra, Mongo, MySQL & much more; Use OSS agents and metrics libraries like collectd, StatsD, etc; Provides OSS libraries in Java, Python, Go, Node, Ruby, etc; Provides OSS proxy to consume existing metrics; REST API;
Statistics
Stacks 21.0K	Stacks 9.6K	Stacks 53
Followers 8.7K	Followers 8.2K	Followers 110
Votes 1.9K	Votes 861	Votes 22
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 5 Scalability 5 High cardinality 4 Fastest alerts 4 World class customer support 4 Easy to install
Integrations
No integrations available	NGINX Google App Engine Apache HTTP Server Java Docker Pingdom MySQL Ruby Python Memcached	Golang Redis VictorOps AWS OpsWorks Amazon Route 53 Kafka Python Chef PagerDuty Amazon SQS

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