StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. DevOps
  3. Monitoring
  4. Monitoring Tools
  5. Ambari vs OpenTracing

Ambari vs OpenTracing

OverviewComparisonAlternatives

Overview

Ambari
Ambari
Stacks44
Followers74
Votes2
OpenTracing
OpenTracing
Stacks243
Followers101
Votes0
GitHub Stars3.5K
Forks315

Ambari vs OpenTracing: What are the differences?

<Ambari and OpenTracing are two different tools used in the field of data and application monitoring and management. Ambari is a management platform for provisioning, managing, and monitoring Apache Hadoop clusters, while OpenTracing is a vendor-neutral open standard for distributed tracing. Here are the key differences between Ambari and OpenTracing:>

  1. Scope of Monitoring: Ambari focuses on monitoring and managing Apache Hadoop clusters, including services like HDFS, YARN, MapReduce, and Hive, among others. On the other hand, OpenTracing is designed for monitoring and tracing application-level transactions and interactions in distributed systems, providing insights into the performance and behavior of microservices and applications.

  2. Granularity of Monitoring: In Ambari, the monitoring granularity is at the cluster level, allowing users to view and manage the overall health and performance of the entire Hadoop cluster. OpenTracing, on the other hand, offers a more fine-grained monitoring approach, capturing detailed information about individual application requests and transactions across distributed components.

  3. Data Visualization: Ambari provides graphical user interfaces and dashboards for visualizing cluster metrics, configurations, and alerts in a centralized manner, making it easier for administrators to monitor and manage the health of Hadoop clusters. OpenTracing mainly focuses on capturing and tracing data for performance analysis and debugging, offering tools and libraries for collecting distributed traces and visualizing the flow of requests through microservices.

In Summary, Ambari is a platform for managing and monitoring Hadoop clusters, while OpenTracing is a standard for distributed tracing for application-level monitoring in distributed systems.

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)
or
Manual

Detailed Comparison

Ambari
Ambari
OpenTracing
OpenTracing

This project is aimed at making Hadoop management simpler by developing software for provisioning, managing, and monitoring Apache Hadoop clusters. It provides an intuitive, easy-to-use Hadoop management web UI backed by its RESTful APIs.

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

Alerts; Ambari Python Libraries; Automated Kerberizaton; Blueprints; Configurations; Service Dashboards; Metrics
-
Statistics
GitHub Stars
-
GitHub Stars
3.5K
GitHub Forks
-
GitHub Forks
315
Stacks
44
Stacks
243
Followers
74
Followers
101
Votes
2
Votes
0
Pros & Cons
Pros
  • 2
    Ease of use
No community feedback yet
Integrations
Hadoop
Hadoop
Ubuntu
Ubuntu
Debian
Debian
Golang
Golang

What are some alternatives to Ambari, OpenTracing?

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).

Related Comparisons

GitHub
Bitbucket

Bitbucket vs GitHub vs GitLab

GitHub
Bitbucket

AWS CodeCommit vs Bitbucket vs GitHub

Kubernetes
Rancher

Docker Swarm vs Kubernetes vs Rancher

gulp
Grunt

Grunt vs Webpack vs gulp

Graphite
Kibana

Grafana vs Graphite vs Kibana