Kibana vs Thanos

Overview

Kibana

Stacks20.6K

Followers16.4K

Votes262

GitHub Stars20.8K

Forks8.5K

Thanos

Stacks100

Followers126

Votes0

Kibana vs Thanos: What are the differences?

Key difference between Kibana and Thanos: Kibana is a data visualization platform that provides a user-friendly interface to explore, analyze, and visualize data stored in ElasticSearch. On the other hand, Thanos is a scalable, highly available, and durable Prometheus platform that provides long-term storage and global query capabilities.
Integration capabilities: Kibana integrates seamlessly with the Elastic Stack, allowing users to leverage the full power of ElasticSearch for data storage and retrieval. Thanos, on the other hand, integrates with Prometheus, extending its capabilities with long-term storage and cross-cluster query support.
Storage architecture: Kibana relies on ElasticSearch for data storage, utilizing its distributed and scalable architecture. In contrast, Thanos introduces a global-scale storage architecture by leveraging object storage systems like Amazon S3 or Google Cloud Storage, which enables efficient querying across multiple Prometheus instances.
Data retention: Kibana does not provide specialized features for long-term data retention and relies on the capabilities of ElasticSearch for data persistence. However, Thanos is specifically designed for long-term data retention, allowing users to store and query data over extended periods efficiently.
Horizontal scalability: Kibana achieves horizontal scalability by deploying multiple instances and configuring load balancers. In contrast, Thanos scales horizontally by distributing query workload across multiple Prometheus instances and coordinating data retrieval from the backend storage.
Federation support: Thanos introduces the concept of federation, enabling efficient querying across multiple Prometheus servers by merging the results of individual Prometheus queries. Kibana, on the other hand, does not have built-in federation support.

In summary, Kibana is a data visualization platform integrated with ElasticSearch, while Thanos is a scalable Prometheus platform with long-term storage and global query capabilities. Their key differences lie in integration capabilities, storage architecture, data retention, horizontal scalability, and federation support.

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Advice on Kibana, Thanos

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.

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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

StackShare

Jun 25, 2019

Needs advice

From a StackShare Community member: “We need better analytics & insights into our Elasticsearch cluster. Grafana, which ships with advanced support for Elasticsearch, looks great but isn’t officially supported/endorsed by Elastic. Kibana, on the other hand, is made and supported by Elastic. I’m wondering what people suggest in this situation."

663k views663k

Comments

Detailed Comparison

Kibana	Thanos
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.	Thanos is a set of components that can be composed into a highly available metric system with unlimited storage capacity. It can be added seamlessly on top of existing Prometheus deployments and leverages the Prometheus 2.0 storage format to cost-efficiently store historical metric data in any object storage while retaining fast query latencies. Additionally, it provides a global query view across all Prometheus installations and can merge data from Prometheus HA pairs on the fly.
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	Global querying view across all connected Prometheus servers; Deduplication and merging of metrics collected from Prometheus HA pairs; Seamless integration with existing Prometheus setups; Any object storage as its only, optional dependency; Downsampling historical data for massive query speedup; Cross-cluster federation; Fault-tolerant query routing; Simple gRPC "Store API" for unified data access across all metric data; Easy integration points for custom metric providers
Statistics
GitHub Stars 20.8K	GitHub Stars -
GitHub Forks 8.5K	GitHub Forks -
Stacks 20.6K	Stacks 100
Followers 16.4K	Followers 126
Votes 262	Votes 0
Pros & Cons
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 Elasticsearch is huge 4 Works on top of elastic only 3 Hardweight UI	No community feedback yet
Integrations
Logstash Elasticsearch Beats	Prometheus

What are some alternatives to Kibana, Thanos?

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.

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).

Jaeger

Jaeger, a Distributed Tracing System

Related Comparisons

Kibana vs Thanos: What are the differences?

Key difference between Kibana and Thanos: Kibana is a data visualization platform that provides a user-friendly interface to explore, analyze, and visualize data stored in ElasticSearch. On the other hand, Thanos is a scalable, highly available, and durable Prometheus platform that provides long-term storage and global query capabilities.
Integration capabilities: Kibana integrates seamlessly with the Elastic Stack, allowing users to leverage the full power of ElasticSearch for data storage and retrieval. Thanos, on the other hand, integrates with Prometheus, extending its capabilities with long-term storage and cross-cluster query support.
Storage architecture: Kibana relies on ElasticSearch for data storage, utilizing its distributed and scalable architecture. In contrast, Thanos introduces a global-scale storage architecture by leveraging object storage systems like Amazon S3 or Google Cloud Storage, which enables efficient querying across multiple Prometheus instances.
Data retention: Kibana does not provide specialized features for long-term data retention and relies on the capabilities of ElasticSearch for data persistence. However, Thanos is specifically designed for long-term data retention, allowing users to store and query data over extended periods efficiently.
Horizontal scalability: Kibana achieves horizontal scalability by deploying multiple instances and configuring load balancers. In contrast, Thanos scales horizontally by distributing query workload across multiple Prometheus instances and coordinating data retrieval from the backend storage.
Federation support: Thanos introduces the concept of federation, enabling efficient querying across multiple Prometheus servers by merging the results of individual Prometheus queries. Kibana, on the other hand, does not have built-in federation support.

Kibana vs Thanos

Overview