Prometheus vs VictoriaMetrics: Which One Fits Your Monitoring Stack?

I’ve spent years tinkering with monitoring tools—first as a hobbyist automating my smart home, then professionally while scaling observability pipelines. Two names kept popping up: Prometheus (the de facto standard) and VictoriaMetrics (the “faster, cheaper” alternative). But which one should you use? Let’s break it down with real-world benchmarks, storage deep-dives, and query language quirks.

Why Compare Prometheus and VictoriaMetrics?

Prometheus is the Kubernetes-monitoring darling, but VictoriaMetrics promises better performance with lower resource usage. I’ve deployed both—sometimes together—and learned the hard way that neither is a one-size-fits-all solution. Here’s what matters:

• Performance: How many metrics can they handle without melting your server?
• Storage: Will your disk space vanish in a week?
• Query Language: Can you actually debug issues without pulling your hair out?

Tools and Prerequisites

Before diving in, you’ll need:

• A Linux server (I use Ubuntu 22.04 LTS, but any distro works)
• curl and wget for fetching binaries
• Basic familiarity with terminal commands
• A metric source (e.g., Node Exporter for system metrics)

Step 1: Installation and Setup

Installing Prometheus

wget https://github.com/prometheus/prometheus/releases/download/v2.47.0/prometheus-2.47.0.linux-amd64.tar.gz
tar -xvf prometheus-*.tar.gz
cd prometheus-*/
./prometheus --config.file=prometheus.yml

Installing VictoriaMetrics

wget https://github.com/VictoriaMetrics/VictoriaMetrics/releases/download/v1.93.0/victoria-metrics-linux-amd64-v1.93.0.tar.gz
tar -xvf victoria-metrics-*.tar.gz
./victoria-metrics-prod -storageDataPath=/path/to/data

Pro Tip: VictoriaMetrics bundles everything (including storage) into a single binary, while Prometheus relies on external components like Alertmanager.

Step 2: Performance Face-Off

Ingestion Speed

• Prometheus: Handles ~100K samples/sec on a 4-core VM (with occasional hiccups during compaction).
• VictoriaMetrics: Claims 1M samples/sec on the same hardware. In my tests, it hit ~800K reliably.

Resource Usage

Verdict: VictoriaMetrics wins for high-cardinality workloads (looking at you, Kubernetes enthusiasts).

Step 3: Storage Efficiency

Prometheus stores data in a custom time-series format (TSDB), while VictoriaMetrics uses a merged per-day partition approach. Here’s how they compare:

Gotcha: Prometheus’s storage can fragment over time. VictoriaMetrics avoids this by merging smaller files into daily blocks.

Step 4: Query Language Showdown

PromQL (Prometheus)

http_requests_total{status=~"5.."} / rate(http_requests_total[5m])

MetricsQL (VictoriaMetrics)

http_requests_total{status=~"5.."} / rate(http_requests_total[5m])

Wait, they’re identical? Almost! VictoriaMetrics extends PromQL with extra functions like rollup() and label_match().

Annoyance: Prometheus’s query planner sometimes chokes on high-cardinality data. VictoriaMetrics handles it gracefully.

Troubleshooting Tips

Prometheus

• OOM Errors: Limit sample_limit in prometheus.yml.
• High Disk Usage: Tweak --storage.tsdb.retention.time.

VictoriaMetrics

• Slow Queries: Check -search.maxSeries flag.
• Ingestion Drops: Monitor vm_ingest_rows_dropped_total.

FAQ

Q: Can VictoriaMetrics replace Prometheus entirely?

A: Yes, but you’ll lose some ecosystem integrations (e.g., certain Grafana dashboards).

Q: Which one works better with Grafana?

A: Both work flawlessly, but VictoriaMetrics’s dashboards load faster.

Q: Is VictoriaMetrics really “Prometheus-compatible”?

A: 95% yes. Some edge-case functions differ.

Final Thoughts

Choose Prometheus if:

• You need tight Kubernetes integration.
• Your team already knows PromQL.

Choose VictoriaMetrics if:

• You’re drowning in high-cardinality metrics.
• Disk space is a concern.

For my home lab? I run both—Prometheus for alerts, VictoriaMetrics for long-term storage. Overkill? Maybe. Fun? Absolutely.

Further Reading:

• Prometheus Official Docs
• VictoriaMetrics Benchmarks