Prometheus vs Zabbix
Compare Prometheus and Zabbix for metrics collection, exporters and agents, network discovery, alerts, retention and the work of operating a monitoring stack.
Which monitoring approach fits?
Choose Prometheus for a metrics-centred architecture when its collection model, PromQL and alerting components suit the services. Choose Zabbix when its integrated discovery, templates, agents and agentless checks fit a mixed IT estate. Both can monitor overlapping systems, and Zabbix can consume Prometheus-format metrics. The decision is about collection and operating workflow, not a claim that one can only monitor servers and the other can only monitor applications.
Seven differences that change the shortlist
| Buying question | Prometheus | Zabbix |
|---|---|---|
| Starting model | Numeric time-series metrics with labels and PromQL | Integrated monitoring with items, templates, triggers and actions |
| Typical collection | Scrape supported targets and exporters | Agents, agentless checks, SNMP and other supported methods |
| Discovery | Configure service discovery for the chosen environment | Configure network and low-level discovery and templates |
| Query and alerting | PromQL and rules; Alertmanager handles alert routing | Items, triggers, dependencies and configured actions |
| Remote estates | Design reachable targets and any remote-storage architecture | Use the required server and proxy arrangement |
| Software access | Open-source software; infrastructure and operations separate | AGPLv3 software; commercial support and hosting separate |
| Signal boundary | Not a raw log or distributed trace store | Do not assume every log or tracing requirement is included |
Four worked buying briefs
These are hypothetical scenarios with explicit assumptions. They do not establish equal capabilities, measured usability or a negotiated price.
| Requirement | Proposed exercise | Accept when |
|---|---|---|
| Metric design | Inspect labels and a representative service query | The metric answers the question without uncontrolled dimensions |
| Remote coverage | Map discovery and collection for one branch | Targets, access and connectivity are explicit |
| Missing data | Stop a permitted test source | The right owner receives a meaningful alert |
| Recovery | Review and rehearse the monitoring restore procedure | Configuration and required history can be recovered |
Service latency
Can the team express a useful service metric without uncontrolled labels?
Prometheus: Instrument the selected service and inspect label cardinality before writing the query.
Zabbix: Collect the required metrics through the chosen item or integration setup.
Use bounded labels; request IDs are not an appropriate default metric dimension.
Branch equipment
Can the team discover and monitor switches at a remote site?
Prometheus: Plan exporter placement, target discovery and connectivity.
Zabbix: Plan the proxy, discovery, SNMP access and templates.
Document firewall and credential ownership rather than assuming the main server can reach every device.
Silent target
What does the engineer receive when collection stops?
Prometheus: Define missing-target or missing-data rules and Alertmanager routing.
Zabbix: Define the missing-data trigger and corresponding action.
Prove that a missing measurement is not silently treated as a healthy zero.
Recovery and history
Can the monitoring service recover with useful retained history?
Prometheus: Document configuration, local data and any remote-storage recovery path.
Zabbix: Document database, configuration and proxy recovery requirements.
Use an approved test environment and record recovery ownership; this comparison contains no recovery-time measurements.
Choose the collection workflow
Prometheus is built around labelled time-series metrics and scraping. Exporters make many systems available to that model, but somebody must maintain target discovery, exporter configuration and the questions expressed in PromQL. Count that work when evaluating a mixed estate.
Zabbix brings discovery, templates, agents, proxies and alert actions into an integrated monitoring system. Those features still require correct templates, credentials, dependencies and item configuration. Its ability to consume Prometheus-format metrics also means these products are not mutually exclusive at the collection boundary.
Free software still needs an operator
Define who owns the monitoring database or time-series storage, upgrades, credentials, backup and capacity. Decide what happens when monitoring itself is unavailable. A free licence does not provide a staffed incident response or unlimited durable storage.
Keep log and trace requirements separate from a generic monitoring checkbox. Prometheus stores metrics rather than raw logs or distributed traces. Zabbix covers a wide range of monitoring checks, but the intended investigation still needs to be demonstrated. Name additional components when the proposed incident path depends on them.
Questions before you choose
Is Prometheus a log database?
No. Its core is numeric time-series metrics. A raw log or distributed tracing requirement needs an appropriate additional system.
Can Zabbix use Prometheus-format metrics?
Yes, supported collection can consume Prometheus-format data. Check the actual item configuration and supported version for the intended source.
Is current Zabbix still GPLv2 software?
Zabbix moved to AGPLv3 from version 7.0. Check the licence of the exact version and distinguish software access from commercial support or hosting.
Your practical evaluation pack
Download the monitoring checklist (CSV)
Four proposed checks with blank evidence and owner columns. Record the actual deployment, package, telemetry volume and retention in your evaluation.
Turn the comparison into your own evaluation
Use the same criteria and priorities for both products, keep unknowns unassessed and record the plan and evidence behind your ratings.
Build a Prometheus vs Zabbix scorecard →Keep the assumptions with the figures
Use the date, billing cycle, units and limits with each example. Check current account terms before purchasing. Unverified prices and model costs stay unpriced.
Download the buying examples as JSON ↓Share the comparison
Use these examples when discussing the shortlist with your team.