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Kibana vs Seq: What are the differences?

Introduction:

Kibana and Seq are both powerful tools used for log management and analysis. While they serve similar purposes, there are key differences between the two.

  1. User Interface Experience: One of the major differences between Kibana and Seq is their user interface experience. Kibana provides a highly customizable and visually appealing interface with various data visualization capabilities. It offers a wide range of graphs, charts, maps, and dashboards that can be customized based on user requirements. On the other hand, Seq focuses more on simplicity and ease of use, providing a clean and intuitive interface that allows for easy log exploration and analysis.

  2. Data Exploration and Search: Kibana and Seq differ in their approach to data exploration and search. Kibana relies on Elasticsearch as the underlying search engine, providing powerful filtering and search capabilities. It allows users to build complex queries using Elasticsearch Query DSL and provides a flexible search syntax. In contrast, Seq has its own built-in search engine, which simplifies the search experience by providing a straightforward and intuitive search syntax. It also supports structured log data exploration using structured query operators.

  3. Data Visualization and Dashboards: Kibana shines in its data visualization capabilities. It offers a wide range of visualization options, including bar charts, line graphs, pie charts, and more. Users can create interactive dashboards by combining multiple visualizations and easily share them with others. Seq, on the other hand, focuses more on log analysis and does not offer as many visualization options as Kibana. While it provides some basic charting capabilities, its primary focus is on providing insights into log data.

  4. Alerting and Monitoring: Kibana and Seq differ in their alerting and monitoring capabilities. Kibana provides a robust alerting framework that allows users to define conditions and triggers based on log data. It supports various notification channels, such as email, Slack, and PagerDuty, for alert delivery. Additionally, Kibana offers monitoring capabilities through its integration with the Elastic Stack, allowing users to monitor the health and performance of their log data infrastructure. In contrast, Seq does not offer native alerting and monitoring features. It primarily focuses on log analysis and exploration.

  5. Scalability and Performance: Kibana and Seq differ in their scalability and performance characteristics. Kibana is designed to handle large volumes of log data and can be horizontally scaled by adding more Elasticsearch nodes. It can handle real-time data ingestion and provides fast search and visualization capabilities. On the other hand, Seq is optimized for small to medium-sized log data volumes and performs best in a single-node setup. It may not be as performant or scalable as Kibana when dealing with high volumes of log data.

  6. Integration with Log Sources: Another key difference between Kibana and Seq is their integration with log sources. Kibana has strong integration with the Elastic Stack ecosystem, particularly with Elasticsearch, Logstash, and Beats. It can seamlessly ingest log data from various sources and provide powerful analysis capabilities. Seq, on the other hand, is primarily focused on .NET and Serilog logs. While it can ingest logs from other sources via custom integrations, its core functionality revolves around analyzing .NET logs.

In Summary, Kibana provides a highly customizable user interface, advanced data exploration and visualization capabilities, robust alerting and monitoring features, good scalability and performance with Elasticsearch, and strong integration with the Elastic Stack. On the other hand, Seq offers a simple and intuitive user interface, straightforward search and analysis capabilities, basic data visualization options, no native alerting and monitoring features, optimized performance for small to medium-sized log data volumes, and a primary focus on .NET log analysis.

Advice on Kibana and Seq
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
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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 · 600.1K 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 Kibana
Pros of Seq
  • 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
  • 5
    Easy to install and configure
  • 5
    Easy to use
  • 3
    Flexible query language
  • 2
    Free unlimited one-person version
  • 2
    Beautiful charts and dashboards
  • 2
    Extensive plug-ins and integrations

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Cons of Kibana
Cons of Seq
  • 6
    Unintuituve
  • 4
    Elasticsearch is huge
  • 3
    Hardweight UI
  • 3
    Works on top of elastic only
  • 1
    It is not free

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- No public GitHub repository available -

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 Seq?

Seq is a self-hosted server for structured log search, analysis, and alerting. It can be hosted on Windows or Linux/Docker, and has integrations for most popular structured logging libraries.

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May 21 2019 at 12:20AM

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What are some alternatives to Kibana and Seq?
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!
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.
Loggly
It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.
Graylog
Centralize and aggregate all your log files for 100% visibility. Use our powerful query language to search through terabytes of log data to discover and analyze important information.
Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
See all alternatives