Grafana vs Kibana vs Logstash

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Grafana

17.9K
14.3K
+ 1
415
Kibana

20.4K
16.2K
+ 1
262
Logstash

11.4K
8.7K
+ 1
103

Grafana vs Kibana vs Logstash: What are the differences?

Introduction

Grafana, Kibana, and Logstash are all popular data visualization and analytics tools used in the field of data analysis. Each of them serves a different purpose and has its own unique features. In this Markdown code, we will discuss the key differences between Grafana, Kibana, and Logstash.

  1. Data Sources: Grafana primarily focuses on time-series data and can connect to various databases, cloud services, and APIs to retrieve data for visualization and analysis. Kibana, on the other hand, is specifically designed for Elasticsearch and is used to analyze and visualize data stored in Elasticsearch indices. Logstash acts as a data pipeline, enabling the ingestion of data from various sources and subsequently transforming and enriching it before sending it to Elasticsearch or other outputs.

  2. Visualization Capabilities: Grafana provides a rich set of visualization options, including interactive dashboards, graphs, heat maps, and alerting features. It offers a wide range of pre-built panels and supports custom panels. Kibana also offers a diverse set of visualizations such as bar charts, line charts, heat maps, and maps. It additionally provides features like coordinate maps and tag clouds. Logstash mainly focuses on data processing and transformation rather than visualization.

  3. Data Transformation and Enrichment: Logstash is a powerful tool for data transformation and enrichment. It enables users to perform various operations on the incoming data, such as parsing, filtering, and adding additional fields. Grafana and Kibana, although they both support some advanced data transformations, do not have the extensive range of data processing capabilities that Logstash offers.

  4. Built-in vs. Standalone Tools: Grafana and Kibana are both standalone tools that can be directly installed and used for data visualization and analysis. Grafana provides a user-friendly interface, allowing users to create and customize dashboards easily. Kibana integrates seamlessly with Elasticsearch, providing the ability to perform complex queries on data stored in Elasticsearch indices. Logstash, on the other hand, is primarily used as part of the ELK (Elasticsearch, Logstash, Kibana) stack, where it serves as the data processing component.

  5. Data Collection and Ingestion: Grafana does not have built-in data collection capabilities and relies on data sources to provide the required data for visualization. Kibana relies on Elasticsearch to index and store data, which can be ingested from various sources using Logstash. Logstash acts as a central data ingestion tool, collecting and processing data from numerous sources, including log files, databases, and message queues.

  6. Community and Ecosystem: Grafana and Kibana both have active communities and a wide range of plugins and extensions available. Grafana has a strong community with numerous plugins developed by third-party developers and offers a marketplace for extensions. Kibana also has an active open-source community with a variety of plugins and integrations available. Logstash benefits from being part of the ELK stack and has a supportive community, although it may not have the same level of plugin and extension availability as Grafana and Kibana.

In summary, Grafana is a versatile tool for time-series data visualization, while Kibana is specifically designed for analyzing data stored in Elasticsearch. Logstash, in contrast, is primarily used for data collection, transformation, and enrichment. Each tool serves a different purpose and has its own unique features, making them suitable for different use cases in the field of data analysis.

Advice on Grafana, Kibana, and Logstash
Susmita Meher
Senior SRE at African Bank · | 4 upvotes · 829.1K views
Needs advice
on
GrafanaGrafanaGraphiteGraphite
and
PrometheusPrometheus

Looking for a tool which can be used for mainly dashboard purposes, but here are the main requirements:

  • Must be able to get custom data from AS400,
  • Able to display automation test results,
  • System monitoring / Nginx API,
  • Able to get data from 3rd parties DB.

Grafana is almost solving all the problems, except AS400 and no database to get automation test results.

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Replies (1)
Sakti Behera
Technical Specialist, Software Engineering at AT&T · | 3 upvotes · 614.6K views
Recommends
on
GrafanaGrafanaPrometheusPrometheus

You can look out for Prometheus Instrumentation (https://prometheus.io/docs/practices/instrumentation/) Client Library available in various languages https://prometheus.io/docs/instrumenting/clientlibs/ to create the custom metric you need for AS4000 and then Grafana can query the newly instrumented metric to show on the dashboard.

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Mat Jovanovic
Head of Cloud at Mats Cloud · | 3 upvotes · 757K views
Needs advice
on
DatadogDatadogGrafanaGrafana
and
PrometheusPrometheus

We're looking for a Monitoring and Logging tool. It has to support AWS (mostly 100% serverless, Lambdas, SNS, SQS, API GW, CloudFront, Autora, etc.), as well as Azure and GCP (for now mostly used as pure IaaS, with a lot of cognitive services, and mostly managed DB). Hopefully, something not as expensive as Datadog or New relic, as our SRE team could support the tool inhouse. At the moment, we primarily use CloudWatch for AWS and Pandora for most on-prem.

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Replies (2)
Recommends
on
DatadogDatadog

I worked with Datadog at least one year and my position is that commercial tools like Datadog are the best option to consolidate and analyze your metrics. Obviously, if you can't pay the tool, the best free options are the mix of Prometheus with their Alert Manager and Grafana to visualize (that are complementary not substitutable). But I think that no use a good tool it's finally more expensive that use a not really good implementation of free tools and you will pay also to maintain its.

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Lucas Rincon
Recommends
on
InstanaInstana

this is quite affordable and provides what you seem to be looking for. you can see a whole thing about the APM space here https://www.apmexperts.com/observability/ranking-the-observability-offerings/

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Needs advice
on
GrafanaGrafana
and
KibanaKibana

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."

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Replies (7)
Recommends
on
GrafanaGrafana
at

For our Predictive Analytics platform, we have used both Grafana and Kibana

Kibana has predictions and ML algorithms support, so if you need them, you may be better off with Kibana . The multi-variate analysis features it provide are very unique (not available in Grafana).

For everything else, definitely Grafana . Especially the number of supported data sources, and plugins clearly makes Grafana a winner (in just visualization and reporting sense). Creating your own plugin is also very easy. The top pros of Grafana (which it does better than Kibana ) are:

  • Creating and organizing visualization panels
  • Templating the panels on dashboards for repetetive tasks
  • Realtime monitoring, filtering of charts based on conditions and variables
  • Export / Import in JSON format (that allows you to version and save your dashboard as part of git)
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Recommends
on
KibanaKibana

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

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Bram Verdonck
Recommends
on
GrafanaGrafana
at

After looking for a way to monitor or at least get a better overview of our infrastructure, we found out that Grafana (which I previously only used in ELK stacks) has a plugin available to fully integrate with Amazon CloudWatch . Which makes it way better for our use-case than the offer of the different competitors (most of them are even paid). There is also a CloudFlare plugin available, the platform we use to serve our DNS requests. Although we are a big fan of https://smashing.github.io/ (previously dashing), for now we are starting with Grafana .

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Recommends
on
KibanaKibana

I use Kibana because it ships with the ELK stack. I don't find it as powerful as Splunk however it is light years above grepping through log files. We previously used Grafana but found it to be annoying to maintain a separate tool outside of the ELK stack. We were able to get everything we needed from Kibana.

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Recommends
on
KibanaKibana

Kibana should be sufficient in this architecture for decent analytics, if stronger metrics is needed then combine with Grafana. Datadog also offers nice overview but there's no need for it in this case unless you need more monitoring and alerting (and more technicalities).

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Recommends
on
GrafanaGrafana

I use Grafana because it is without a doubt the best way to visualize metrics

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Povilas Brilius
PHP Web Developer at GroundIn Software · | 0 upvotes · 629.5K views
Recommends
on
KibanaKibana
at

@Kibana, of course, because @Grafana looks like amateur sort of solution, crammed with query builder grouping aggregates, but in essence, as recommended by CERN - KIbana is the corporate (startup vectored) decision.

Furthermore, @Kibana comes with complexity adhering ELK stack, whereas @InfluxDB + @Grafana & co. recently have become sophisticated development conglomerate instead of advancing towards a understandable installation step by step inheritance.

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Pros of Grafana
Pros of Kibana
Pros of Logstash
  • 89
    Beautiful
  • 68
    Graphs are interactive
  • 57
    Free
  • 56
    Easy
  • 34
    Nicer than the Graphite web interface
  • 26
    Many integrations
  • 18
    Can build dashboards
  • 10
    Easy to specify time window
  • 10
    Can collaborate on dashboards
  • 9
    Dashboards contain number tiles
  • 5
    Open Source
  • 5
    Integration with InfluxDB
  • 5
    Click and drag to zoom in
  • 4
    Authentification and users management
  • 4
    Threshold limits in graphs
  • 3
    Alerts
  • 3
    It is open to cloud watch and many database
  • 3
    Simple and native support to Prometheus
  • 2
    Great community support
  • 2
    You can use this for development to check memcache
  • 2
    You can visualize real time data to put alerts
  • 0
    Grapsh as code
  • 0
    Plugin visualizationa
  • 88
    Easy to setup
  • 65
    Free
  • 45
    Can search text
  • 21
    Has pie chart
  • 13
    X-axis is not restricted to timestamp
  • 9
    Easy queries and is a good way to view logs
  • 6
    Supports Plugins
  • 4
    Dev Tools
  • 3
    More "user-friendly"
  • 3
    Can build dashboards
  • 2
    Out-of-Box Dashboards/Analytics for Metrics/Heartbeat
  • 2
    Easy to drill-down
  • 1
    Up and running
  • 69
    Free
  • 18
    Easy but powerful filtering
  • 12
    Scalable
  • 2
    Kibana provides machine learning based analytics to log
  • 1
    Great to meet GDPR goals
  • 1
    Well Documented

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Cons of Grafana
Cons of Kibana
Cons of Logstash
  • 1
    No interactive query builder
  • 7
    Unintuituve
  • 4
    Works on top of elastic only
  • 4
    Elasticsearch is huge
  • 3
    Hardweight UI
  • 4
    Memory-intensive
  • 1
    Documentation difficult to use

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What is 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.

What is 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.

What is Logstash?

Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.

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What are some alternatives to Grafana, Kibana, and Logstash?
Datadog
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!
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.
Graphite
Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand
Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
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
See all alternatives