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  5. Kibana vs logz.io

Kibana vs logz.io

OverviewDecisionsComparisonAlternatives

Overview

Kibana
Kibana
Stacks20.6K
Followers16.4K
Votes262
GitHub Stars20.8K
Forks8.5K
logz.io
logz.io
Stacks53
Followers54
Votes0

Kibana vs logz.io: What are the differences?

Introduction:

Kibana and logz.io are both popular tools used for analyzing and visualizing large volumes of data, particularly log data. While they both serve similar purposes, there are several key differences between the two.

  1. Integration: Kibana is an open-source data visualization and exploration tool that works alongside Elasticsearch, a search and analytics engine. It is part of the Elastic Stack and is often used in conjunction with it. On the other hand, logz.io is a cloud-based log management platform that offers a comprehensive stack of tools, including log analytics, visualization, searching, monitoring, and more. It is built around the ELK (Elasticsearch, Logstash, and Kibana) stack but provides a fully managed and hosted solution.

  2. Managed Service vs. Self-Hosted: Kibana is typically self-hosted, which means that organizations need to set up and manage their own infrastructure, including Elasticsearch and Kibana instances. This allows for greater customization and control but can require significant resources and expertise. In contrast, logz.io is a managed service, taking away the burden of infrastructure management, maintenance, and scalability from users. Organizations can simply send their logs to logz.io and leverage its fully managed and scalable platform.

  3. Ease of Use: Kibana, being an open-source tool, requires some level of technical expertise to set up, configure, and use effectively. It offers a wide range of features and flexibility but may have a steeper learning curve for beginners. Logz.io, with its managed service approach, focuses on providing a user-friendly interface and ease of use. It simplifies the setup process and offers intuitive navigation and visualizations, making it more accessible to users with varying levels of technical expertise.

  4. Security and Compliance: Kibana provides a range of security features, including role-based access control (RBAC), encryption, and authentication options. However, the responsibility of implementing and managing these security measures lies with the users. Logz.io, as a managed service, offers built-in security and compliance features, including encryption at rest and in transit, access control, and compliance with various industry standards such as SOC 2, GDPR, and ISO 27001. This makes it a suitable choice for organizations with strict security and compliance requirements.

  5. Pricing Model: Kibana is an open-source tool, meaning it is available for free to download and use. However, organizations need to bear the costs associated with setting up and managing their own infrastructure. Logz.io, being a managed service, follows a subscription-based pricing model. The cost is based on factors such as data volume, retention, and specific features required. This provides organizations with predictable pricing and eliminates the need for upfront hardware or infrastructure investments.

  6. Additional Features: While Kibana primarily focuses on data visualization and exploration, logz.io offers a more comprehensive set of features tailored specifically for log management. These additional features include log parsing, automated parsing updates, anomaly detection, machine learning-based insights, alerting, integrations with popular platforms such as Slack and PagerDuty, and more. These features enhance the log analysis capabilities of logz.io and provide a more holistic log management solution.

In summary, while Kibana is an open-source tool designed for data visualization and exploration, logz.io offers a fully managed log management platform with additional features, enhanced ease of use, security and compliance measures, and a subscription-based pricing model.

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Advice on Kibana, logz.io

matteo1989it
matteo1989it

Jun 26, 2019

ReviewonKibanaKibanaGrafanaGrafanaElasticsearchElasticsearch

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
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
abrahamfathman
abrahamfathman

Jun 26, 2019

ReviewonKibanaKibanaSplunkSplunkGrafanaGrafana

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.

2.29M views2.29M
Comments

Detailed Comparison

Kibana
Kibana
logz.io
logz.io

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.

It provides Elasticsearch, Logstash and Kibana on the cloud with alerts, unlimited scalability and free ELK apps. Index, search & visualize your data.

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
-
Statistics
GitHub Stars
20.8K
GitHub Stars
-
GitHub Forks
8.5K
GitHub Forks
-
Stacks
20.6K
Stacks
53
Followers
16.4K
Followers
54
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
Logstash
Elasticsearch
Elasticsearch
Beats
Beats
No integrations available

What are some alternatives to Kibana, logz.io?

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.

Papertrail

Papertrail

Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.

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.

Logmatic

Logmatic

Get a clear overview of what is happening across your distributed environments, and spot the needle in the haystack in no time. Build dynamic analyses and identify improvements for your software, your user experience and your business.

Loggly

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.

Logentries

Logentries

Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users.

Logstash

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.

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

Graylog

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.

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