Need advice about which tool to choose?Ask the StackShare community!

Kibana

20.2K
16K
+ 1
262
Loggly

274
302
+ 1
168
Add tool

Kibana vs Loggly: What are the differences?

Introduction

Here, we will focus on the key differences between Kibana and Loggly as two popular log management and analytics tools.

  1. Deployment and Hosting: Kibana is an open-source tool developed by Elastic and can be self-hosted or hosted on platforms like Elastic Cloud. On the other hand, Loggly is a cloud-based log management solution, where the entire infrastructure and hosting are handled by Loggly.

  2. Search and Querying: Kibana provides a powerful search and querying interface with its Elasticsearch integration. It offers a wide range of advanced search capabilities, including full-text search, filtering, and aggregations. Loggly also offers searching and querying features, but it focuses more on speed and simplicity, providing pre-built search filters and the ability to construct queries using standard search syntax.

  3. Visualization and Dashboards: Kibana is well-known for its rich visualization features. It offers an extensive collection of visualization options, including line charts, bar charts, maps, and more. With its drag-and-drop dashboard builder, users can create interactive and personalized dashboards. Loggly, however, has a more limited set of visualization capabilities. It offers basic charting and graphing options, but it doesn't have the same level of customization or variety as Kibana.

  4. Alerting and Monitoring: Kibana lacks built-in alerting and monitoring features by default. It relies on external integrations or plugins, such as Elasticsearch Watcher or third-party tools, to enable alerting and monitoring. On the other hand, Loggly provides built-in alerting functionality, allowing users to set up alerts based on specific log events or patterns, and receive notifications via various channels like email or Slack.

  5. Log Ingestion and Parsing: Kibana relies on Elasticsearch for log ingestion, and it supports different log file formats. By using Logstash, users can preprocess logs before indexing them into Elasticsearch. Loggly, on the other hand, offers various ingestion methods, including bulk upload, syslog, log shippers, and log routing. It also provides automatic parsing and extraction of log events, making it easier to analyze and search through log data without much configuration.

  6. Ease of Use and Learning Curve: Kibana has a steeper learning curve compared to Loggly, primarily due to its advanced features and flexibility. It requires some knowledge of Elasticsearch and the query language. Loggly, on the other hand, has a more user-friendly interface and offers a simpler setup process, making it easier for non-technical users or those new to log management to get started quickly.

In Summary, Kibana and Loggly have notable differences in deployment, search capabilities, visualization, alerting, log ingestion, and ease of use. These variations make them suitable for different use cases and user preferences.

Advice on Kibana and Loggly
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."

See more
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)
See more
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

See more
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 .

See more
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.

See more
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).

See more
Recommends
on
GrafanaGrafana

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

See more
Povilas Brilius
PHP Web Developer at GroundIn Software · | 0 upvotes · 602.7K 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.

See more
Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn More
Pros of Kibana
Pros of Loggly
  • 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
  • 37
    Centralized log management
  • 25
    Easy to setup
  • 21
    Great filtering
  • 16
    Live logging
  • 15
    Json log support
  • 10
    Log Management
  • 10
    Alerting
  • 7
    Great Dashboards
  • 7
    Love the product
  • 4
    Heroku Add-on
  • 2
    Easy to setup and use
  • 2
    Easy setup
  • 2
    No alerts in free plan
  • 2
    Great UI
  • 2
    Good parsing
  • 2
    Powerful
  • 2
    Fast search
  • 2
    Backup to S3

Sign up to add or upvote prosMake informed product decisions

Cons of Kibana
Cons of Loggly
  • 6
    Unintuituve
  • 4
    Elasticsearch is huge
  • 3
    Hardweight UI
  • 3
    Works on top of elastic only
  • 3
    Pricey after free plan

Sign up to add or upvote consMake informed product decisions

- 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 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.

Need advice about which tool to choose?Ask the StackShare community!

What companies use Kibana?
What companies use Loggly?
See which teams inside your own company are using Kibana or Loggly.
Sign up for StackShare EnterpriseLearn More

Sign up to get full access to all the companiesMake informed product decisions

What tools integrate with Kibana?
What tools integrate with Loggly?

Sign up to get full access to all the tool integrationsMake informed product decisions

Blog Posts

May 21 2019 at 12:20AM

Elastic

ElasticsearchKibanaLogstash+4
12
5185
GitHubPythonReact+42
49
40767
GitHubGitPython+22
17
14221
JavaScriptGitHubGit+33
20
2090
GitHubMySQLSlack+44
109
50678
What are some alternatives to Kibana and Loggly?
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.
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.
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.
See all alternatives