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  1. Stackups
  2. DevOps
  3. Monitoring
  4. Monitoring Tools
  5. Cacti vs Logstash

Cacti vs Logstash

OverviewComparisonAlternatives

Overview

Cacti
Cacti
Stacks89
Followers202
Votes10
Logstash
Logstash
Stacks12.3K
Followers8.8K
Votes103
GitHub Stars14.7K
Forks3.5K

Cacti vs Logstash: What are the differences?

Introduction

Cacti and Logstash are both powerful tools used in monitoring and analyzing data, yet they excel in different aspects based on their unique functionalities. Below are the key differences between Cacti and Logstash.

1. Data Collection:

Cacti primarily focuses on network monitoring and data collection through SNMP (Simple Network Management Protocol), making it suitable for infrastructure monitoring. On the other hand, Logstash specializes in log collection and aggregation from various sources, providing insights into application performance and system behavior.

2. Data Processing:

While Cacti offers basic graphing capabilities for monitoring network metrics, Logstash stands out with its advanced data processing features. Logstash allows users to filter, parse, and transform data in real-time, enabling more intricate analysis and customization compared to Cacti.

3. Flexibility:

Cacti mainly works with SNMP-enabled devices, limiting its flexibility in data sources. In contrast, Logstash supports a wide range of data inputs, including logs, metrics, events, and more, making it a versatile tool for data collection and analysis across different platforms and systems.

4. Scalability:

In terms of scalability, Logstash is designed to handle large volumes of data efficiently due to its distributed architecture and scaling capabilities. Cacti, while suitable for smaller-scale network monitoring, may encounter limitations when dealing with extensive data sets or multiple data sources.

5. Integration:

Logstash is part of the larger Elastic Stack (ELK), which includes Elasticsearch and Kibana for data storage and visualization. This seamless integration allows users to easily store, search, and analyze data within the ELK ecosystem. In comparison, Cacti lacks built-in integration with other tools for comprehensive data analysis and visualization.

6. Use Cases:

Cacti is well-suited for network administrators and IT professionals looking to monitor network performance and availability using SNMP. On the other hand, Logstash caters to DevOps teams and developers seeking to gather and analyze log data, troubleshoot issues, and gain insights into system operations.

Summary

In summary, Cacti excels in network monitoring with SNMP data collection, while Logstash offers advanced data processing, flexibility with various data sources, scalability for large datasets, integration within the ELK stack, and caters to log analysis for DevOps teams.

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Detailed Comparison

Cacti
Cacti
Logstash
Logstash

Cacti is a complete network graphing solution designed to harness the power of RRDTool's data storage and graphing functionality. Cacti provides a fast poller, advanced graph templating, multiple data acquisition methods, and user management features out of the box.

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.

Unlimited number of graph items can be defined for each graph optionally utilizing CDEFs or data sources from within cacti.;Automatic grouping of GPRINT graph items to AREA, STACK, and LINE[1-3] to allow for quick re-sequencing of graph items.;Auto-Padding support to make sure graph legend text lines up.;Graph data can be manipulated using the CDEF math functions built into RRDTool. These CDEF functions can be defined in cacti and can be used globally on each graph.;Data sources can be created that utilize RRDTool's "create" and "update" functions. Each data source can be used to gather local or remote data and placed on a graph.
Centralize data processing of all types;Normalize varying schema and formats;Quickly extend to custom log formats;Easily add plugins for custom data source
Statistics
GitHub Stars
-
GitHub Stars
14.7K
GitHub Forks
-
GitHub Forks
3.5K
Stacks
89
Stacks
12.3K
Followers
202
Followers
8.8K
Votes
10
Votes
103
Pros & Cons
Pros
  • 3
    Rrdtool based
  • 3
    Free
  • 2
    Fast poller
  • 1
    Graphs from snmp
  • 1
    Graphs from language independent scripts
Pros
  • 69
    Free
  • 18
    Easy but powerful filtering
  • 12
    Scalable
  • 2
    Kibana provides machine learning based analytics to log
  • 1
    Well Documented
Cons
  • 4
    Memory-intensive
  • 1
    Documentation difficult to use
Integrations
RRDtool
RRDtool
Kibana
Kibana
Elasticsearch
Elasticsearch
Beats
Beats

What are some alternatives to Cacti, Logstash?

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.

Kibana

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.

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.

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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