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InfluxDB vs Zabbix: What are the differences?

Introduction:

InfluxDB and Zabbix are two popular tools used for monitoring and managing systems. While both have similar goals, there are several key differences between them.

  1. Data storage model: InfluxDB is a time-series database designed specifically for handling time-based data. It is optimized for storing and querying large amounts of time-stamped data. On the other hand, Zabbix uses a relational database to store its data, which makes it more suitable for handling various types of data beyond just time-stamped measurements.

  2. Monitoring capabilities: Zabbix provides a comprehensive set of monitoring capabilities, including monitoring network devices, servers, applications, and cloud resources. It supports a wide range of monitoring methods such as agent-based, agentless, and SNMP. InfluxDB, on the other hand, focuses primarily on collecting, storing, and querying time-series data, making it more suitable for monitoring and analyzing metrics and events rather than the overall health of a system.

  3. Scalability: InfluxDB is designed to handle high volumes of time-series data and provides built-in mechanisms for horizontal scalability. It supports clustering and sharding, allowing it to handle large-scale deployments. Zabbix, while scalable to some extent, may require additional configurations to achieve the same level of scalability as InfluxDB.

  4. User interface and visualization: Zabbix provides a feature-rich web interface that allows users to configure and customize dashboards, graphs, and reports. It offers a wide range of visualization options and supports flexible drill-down capabilities. InfluxDB, on the other hand, does not provide a built-in user interface for visualization. However, it integrates well with other tools like Grafana, which offer powerful visualization and dashboarding capabilities.

  5. Alerting and notification: Zabbix offers advanced alerting and notification capabilities, allowing users to define complex conditions and actions based on monitored data. It supports various notification methods such as email, SMS, and scripts. InfluxDB, on the other hand, does not have built-in alerting capabilities. However, it can integrate with other tools like Kapacitor, which provide advanced alerting and anomaly detection functionalities.

  6. Ease of installation and configuration: Zabbix may require more manual configuration and setup compared to InfluxDB. It has a more complex setup process and requires additional dependencies such as a relational database and a web server. InfluxDB, on the other hand, provides a simple and straightforward installation process with minimal dependencies, making it easier to get started.

In summary, InfluxDB is a powerful time-series database optimized for handling large amounts of time-stamped data, while Zabbix is a comprehensive monitoring tool that offers a wide range of monitoring capabilities beyond just time-series data. InfluxDB focuses more on data storage and querying, while Zabbix provides a feature-rich user interface, extensive alerting capabilities, and a broader scope of monitoring options.

Advice on InfluxDB and Zabbix
Needs advice
on
CentreonCentreon
and
ZabbixZabbix

My team is divided on using Centreon or Zabbix for enterprise monitoring and alert automation. Can someone let us know which one is better? There is one more tool called Datadog that we are using for cloud assets. Of course, Datadog presents us with huge bills. So we want to have a comparative study. Suggestions and advice are welcome. Thanks!

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Replies (4)
Geoffrey Timmerman
Systems Engineer at Simac · | 6 upvotes · 296.7K views
Recommends
on
ZabbixZabbix
at

I work at Volvo Car Corporation as a consultant Project Manager. We have deployed Zabbix in all of our factories for factory monitoring because after thorough investigation we saw that Zabbix supports the wide variety of Operating Systems, hardware peripherals and devices a Car Manufacturer has.

No other tool had the same amount of support onboard for our production environment and we didn't want to end up using a different tool again for several areas. That is the major strong point about Zabbix and it's free of course. Another strong point is the documentation which is widely available; Zabbix Youtube channel with tutorial video's, Zabbix share which holds free templates, the Zabbix online documentation and the Zabbix forum also helped us out quite a bit. Deployment is quite easy since it uses templates, so almost all configuration can be done on server side.

To conclude, we are really pleased with the tool so far, it helped us detect several causes of issues that were a pain to solve in the past.

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Recommends
on
CentreonCentreon

Centreon is part of the Nagios ecosystem, meaning there is a huge number of resources you may find around in the community (plugins, skills, addons). Zabbix monitoring paradigms are totally different from Centreon. Centreon plugins have some kind of intelligence when they are launched, where Zabbix monitoring rules are configured centrally with the raw data collected. Testing both will help you understand :) Users used to say Centreon may be faster for setup and deployment. And in the end, both are full of monitoring features. Centreon has out of the box a full catalog of probes from cloud to the edge https://www.centreon.com/en/plugins-pack-list/ As soon as you have defined your monitoring policies and template, you can deploy it fast through command line API or REST API. Centreon plays well in the ITSM, Automation, AIOps spaces with many connectors for Prometheus, ServiceNow, GLPI, Ansible, Chef, Splunk, ... The polling server mode is one of the differentiators with Centreon. You set up remote server(s) and chose btw multiple information-exchange mechanisms. Powerful and resilient for remote, VPN, DMZ, satellite networks. Centreon is a good value for price to do a data collection (availability, performance, fault) on a wide range of technologies (physical, legacy, cloud). There are pro support and enterprise version with dashboards and reporting. IT Central Station gathers many user feedback you can rely on both Centreon & Zabbix https://www.itcentralstation.com/products/centreon-reviews  

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muutech
at Muutech Monitoring Solutions, S.L. · | 3 upvotes · 294.1K views
Recommends
on
ZabbixZabbix

We highly recommend Zabbix. We have used it to build our own monitoring product (available on cloud -like datadog- or on premise with support) because of its flexibility and extendability. It can be easily integrated with the powerful dashboarding and data aggregation of Grafana, so it is perfect. All configuration is done via web and templates, so it scales well and can be distributed via proxies. I think there also more companies providing consultancy in Zabbix (like ours) than Centreon and community is much wider. Also Zabbix roadmap and focus (compatibility with Elasticsearch, Prometheus, TimescaleDB) is really really good.

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Recommends
on
KamonKamon
at

Hi Vivek, what's your stack? If huge monitoring bills are your concern and if you’re using a number of JVM languages, or mostly Scala / Akka, and would like “one tool to monitor them all”, Kamon might be the friendliest choice to go for.

Kamon APM’s major benefit is it comes with a built-in dashboard for the most important metrics to monitor, taking the pain of figuring out what to monitor and building your own dashboards for weeks out of the monitoring.

https://kamon.io/apm/

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Needs advice
on
InfluxDBInfluxDBMongoDBMongoDB
and
TimescaleDBTimescaleDB

We are building an IOT service with heavy write throughput and fewer reads (we need downsampling records). We prefer to have good reliability when comes to data and prefer to have data retention based on policies.

So, we are looking for what is the best underlying DB for ingesting a lot of data and do queries easily

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Replies (3)
Yaron Lavi
Recommends
on
PostgreSQLPostgreSQL

We had a similar challenge. We started with DynamoDB, Timescale, and even InfluxDB and Mongo - to eventually settle with PostgreSQL. Assuming the inbound data pipeline in queued (for example, Kinesis/Kafka -> S3 -> and some Lambda functions), PostgreSQL gave us a We had a similar challenge. We started with DynamoDB, Timescale and even InfluxDB and Mongo - to eventually settle with PostgreSQL. Assuming the inbound data pipeline in queued (for example, Kinesis/Kafka -> S3 -> and some Lambda functions), PostgreSQL gave us better performance by far.

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Recommends
on
DruidDruid

Druid is amazing for this use case and is a cloud-native solution that can be deployed on any cloud infrastructure or on Kubernetes. - Easy to scale horizontally - Column Oriented Database - SQL to query data - Streaming and Batch Ingestion - Native search indexes It has feature to work as TimeSeriesDB, Datawarehouse, and has Time-optimized partitioning.

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Ankit Malik
Software Developer at CloudCover · | 3 upvotes · 351.5K views
Recommends
on
Google BigQueryGoogle BigQuery

if you want to find a serverless solution with capability of a lot of storage and SQL kind of capability then google bigquery is the best solution for that.

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Decisions about InfluxDB and Zabbix
Benoit Larroque
Principal Engineer at Sqreen · | 2 upvotes · 144.4K views

I chose TimescaleDB because to be the backend system of our production monitoring system. We needed to be able to keep track of multiple high cardinality dimensions.

The drawbacks of this decision are our monitoring system is a bit more ad hoc than it used to (New Relic Insights)

We are combining this with Grafana for display and Telegraf for data collection

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Pros of InfluxDB
Pros of Zabbix
  • 59
    Time-series data analysis
  • 30
    Easy setup, no dependencies
  • 24
    Fast, scalable & open source
  • 21
    Open source
  • 20
    Real-time analytics
  • 6
    Continuous Query support
  • 5
    Easy Query Language
  • 4
    HTTP API
  • 4
    Out-of-the-box, automatic Retention Policy
  • 1
    Offers Enterprise version
  • 1
    Free Open Source version
  • 21
    Free
  • 9
    Alerts
  • 5
    Service/node/network discovery
  • 5
    Templates
  • 4
    Base metrics from the box
  • 3
    Multi-dashboards
  • 3
    SMS/Email/Messenger alerts
  • 2
    Grafana plugin available
  • 2
    Supports Graphs ans screens
  • 2
    Support proxies (for monitoring remote branches)
  • 1
    Perform website checking (response time, loading, ...)
  • 1
    API available for creating own apps
  • 1
    Templates free available (Zabbix Share)
  • 1
    Works with multiple databases
  • 1
    Advanced integrations
  • 1
    Supports multiple protocols/agents
  • 1
    Complete Logs Report
  • 1
    Open source
  • 1
    Supports large variety of Operating Systems
  • 1
    Supports JMX (Java, Tomcat, Jboss, ...)

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Cons of InfluxDB
Cons of Zabbix
  • 4
    Instability
  • 1
    Proprietary query language
  • 1
    HA or Clustering is only in paid version
  • 5
    The UI is in PHP
  • 2
    Puppet module is sluggish

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What is InfluxDB?

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

What is Zabbix?

Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.

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What companies use InfluxDB?
What companies use Zabbix?
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What are some alternatives to InfluxDB and Zabbix?
TimescaleDB
TimescaleDB: An open-source database built for analyzing time-series data with the power and convenience of SQL — on premise, at the edge, or in the cloud.
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Elasticsearch
Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
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