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  1. Stackups
  2. DevOps
  3. Monitoring
  4. Monitoring Tools
  5. Jaeger vs OpenTracing

Jaeger vs OpenTracing

OverviewComparisonAlternatives

Overview

OpenTracing
OpenTracing
Stacks243
Followers101
Votes0
GitHub Stars3.5K
Forks315
Jaeger
Jaeger
Stacks340
Followers464
Votes25
GitHub Stars22.0K
Forks2.7K

Jaeger vs OpenTracing: What are the differences?

## Introduction
This Markdown document discusses the key differences between Jaeger and OpenTracing.

## 1. **Data Model**:
In Jaeger, the trace data model consists of spans where each span represents a unit of work, while in OpenTracing, the data model is defined in terms of spans, traces, and traces with a single root span.

## 2. **Implementation**:
Jaeger is an open-source distributed tracing system developed by Uber Technologies, focusing on high performance and ease of use, whereas OpenTracing is a vendor-neutral API specification for distributed tracing.

## 3. **Compatibility**:
Jaeger API is fully compatible with the OpenTracing API, meaning that Jaeger can be used as a backend for applications instrumented with OpenTracing-compatible libraries.

## 4. **Visualization**:
Jaeger provides a user interface for visualization and querying of traces, allowing users to interact with trace data effectively, whereas OpenTracing does not provide such visualization capabilities natively.

## 5. **Community Support**:
Jaeger has a vibrant community actively contributing to its development and providing support, while OpenTracing benefits from a broader ecosystem support but lacks a specific community dedicated solely to its advancement.

## 6. **Storage Options**:
Jaeger supports storage backends like Cassandra, Elasticsearch, and Kafka for storing trace data, whereas OpenTracing is focused on defining a common API and does not provide specific recommendations for storage solutions.

Summary, Jaeger and OpenTracing differ in their data models, implementations, compatibility, visualization capabilities, community support, and storage options.

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Detailed Comparison

OpenTracing
OpenTracing
Jaeger
Jaeger

Consistent, expressive, vendor-neutral APIs for distributed tracing and context propagation.

Jaeger, a Distributed Tracing System

Statistics
GitHub Stars
3.5K
GitHub Stars
22.0K
GitHub Forks
315
GitHub Forks
2.7K
Stacks
243
Stacks
340
Followers
101
Followers
464
Votes
0
Votes
25
Pros & Cons
No community feedback yet
Pros
  • 7
    Open Source
  • 7
    Easy to install
  • 6
    Feature Rich UI
  • 5
    CNCF Project
Integrations
Golang
Golang
Golang
Golang
Elasticsearch
Elasticsearch
Cassandra
Cassandra

What are some alternatives to OpenTracing, Jaeger?

Grafana

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

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

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

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

Netdata

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

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

Sensu

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

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

Lumigo

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

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).

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