Jaeger vs OpenTelemetry

Overview

Jaeger

Stacks340

Followers464

Votes25

GitHub Stars22.0K

Forks2.7K

OpenTelemetry

Stacks203

Followers148

Votes4

Jaeger vs OpenTelemetry: What are the differences?

Introducing OpenTelemetry and Jaeger

OpenTelemetry and Jaeger are both open-source observability tools that aim to provide insight into the performance and behavior of modern software systems. While they have some similarities, there are several key differences between the two.

Architecture: OpenTelemetry is designed as a set of APIs, SDKs, and other instrumentation libraries that can be integrated into applications and services, allowing for distributed tracing, metrics collection, and other observability features. On the other hand, Jaeger is a complete tracing platform that consists of a backend storage component, a query service, and instrumentation libraries. This difference in architecture means that OpenTelemetry is more modular and can be integrated into existing systems more easily, while Jaeger provides a more comprehensive tracing solution out of the box.
Vendor Support: OpenTelemetry is a collaborative effort between several major companies, including Microsoft, Google, and Amazon. This level of industry support means that OpenTelemetry is likely to have better long-term support and a wider range of integrations with popular frameworks and libraries. Jaeger, on the other hand, is maintained primarily by the Jaeger community and has fewer resources and commercial backing.
Instrumentation Libraries: OpenTelemetry provides a wide range of instrumentation libraries for various programming languages and frameworks, making it easy to add observability to different types of applications. These libraries are designed to be consistent and provide a unified API. Jaeger, on the other hand, provides its own set of instrumentation libraries, which may not have the same level of compatibility or consistency across different languages and frameworks.
Standardization: OpenTelemetry aims to be a vendor-agnostic and industry-standard solution for observability. It is actively working on defining and implementing standards for distributed tracing, metrics, and other observability areas. This standardization effort makes it easier for developers and operators to adopt and integrate OpenTelemetry into their systems. Jaeger, while widely used and supported, is not part of a broader standardization effort and may have different conventions and practices.
Data Exporters: OpenTelemetry provides a flexible and extensible model for exporting collected telemetry data to various backend systems and analytics platforms. This allows users to choose the most appropriate storage and analysis solutions for their specific needs. Jaeger, on the other hand, has a more limited set of built-in exporters, although it does support exporting data to popular systems like Elasticsearch and Jaeger's own storage backend.
Community Ecosystem: OpenTelemetry benefits from a vibrant and growing community that actively contributes to its development, provides support, and creates additional tools and integrations. This strong community ecosystem ensures that OpenTelemetry will continue to evolve and improve over time. While Jaeger also has a dedicated community, it is not as large or as well-funded as OpenTelemetry's community.

In Summary, OpenTelemetry and Jaeger differ in their architecture, vendor support, instrumentation libraries, standardization efforts, data exporters, and community ecosystem.

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CLI (Node.js)

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Detailed Comparison

Jaeger	OpenTelemetry
Jaeger, a Distributed Tracing System	It provides a single set of APIs, libraries, agents, and collector services to capture distributed traces and metrics from your application. You can analyze them using Prometheus, Jaeger, and other observability tools.
Statistics
GitHub Stars 22.0K	GitHub Stars -
GitHub Forks 2.7K	GitHub Forks -
Stacks 340	Stacks 203
Followers 464	Followers 148
Votes 25	Votes 4
Pros & Cons
Pros 7 Open Source 7 Easy to install 6 Feature Rich UI 5 CNCF Project	Pros 4 OSS
Integrations
Golang Elasticsearch Cassandra	No integrations available

What are some alternatives to Jaeger, OpenTelemetry?

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.

Kibana

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.

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.

Nagios

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

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

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.

Graphite

Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand

Lumigo

Lumigo is an observability platform built for developers, unifying distributed tracing with payload data, log management, and real-time metrics to help you deeply understand and troubleshoot your systems.

StatsD

It is a network daemon that runs on the Node.js platform and listens for statistics, like counters and timers, sent over UDP or TCP and sends aggregates to one or more pluggable backend services (e.g., Graphite).

Related Comparisons

Jaeger vs OpenTelemetry: What are the differences?

Introducing OpenTelemetry and Jaeger

Architecture: OpenTelemetry is designed as a set of APIs, SDKs, and other instrumentation libraries that can be integrated into applications and services, allowing for distributed tracing, metrics collection, and other observability features. On the other hand, Jaeger is a complete tracing platform that consists of a backend storage component, a query service, and instrumentation libraries. This difference in architecture means that OpenTelemetry is more modular and can be integrated into existing systems more easily, while Jaeger provides a more comprehensive tracing solution out of the box.
Vendor Support: OpenTelemetry is a collaborative effort between several major companies, including Microsoft, Google, and Amazon. This level of industry support means that OpenTelemetry is likely to have better long-term support and a wider range of integrations with popular frameworks and libraries. Jaeger, on the other hand, is maintained primarily by the Jaeger community and has fewer resources and commercial backing.
Instrumentation Libraries: OpenTelemetry provides a wide range of instrumentation libraries for various programming languages and frameworks, making it easy to add observability to different types of applications. These libraries are designed to be consistent and provide a unified API. Jaeger, on the other hand, provides its own set of instrumentation libraries, which may not have the same level of compatibility or consistency across different languages and frameworks.
Standardization: OpenTelemetry aims to be a vendor-agnostic and industry-standard solution for observability. It is actively working on defining and implementing standards for distributed tracing, metrics, and other observability areas. This standardization effort makes it easier for developers and operators to adopt and integrate OpenTelemetry into their systems. Jaeger, while widely used and supported, is not part of a broader standardization effort and may have different conventions and practices.
Data Exporters: OpenTelemetry provides a flexible and extensible model for exporting collected telemetry data to various backend systems and analytics platforms. This allows users to choose the most appropriate storage and analysis solutions for their specific needs. Jaeger, on the other hand, has a more limited set of built-in exporters, although it does support exporting data to popular systems like Elasticsearch and Jaeger's own storage backend.
Community Ecosystem: OpenTelemetry benefits from a vibrant and growing community that actively contributes to its development, provides support, and creates additional tools and integrations. This strong community ecosystem ensures that OpenTelemetry will continue to evolve and improve over time. While Jaeger also has a dedicated community, it is not as large or as well-funded as OpenTelemetry's community.

In Summary, OpenTelemetry and Jaeger differ in their architecture, vendor support, instrumentation libraries, standardization efforts, data exporters, and community ecosystem.

Jaeger vs OpenTelemetry

Overview