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OxiPulse vs Telegraf

By SecuryBlack

Telegraf is an impressive piece of software. Written in Go and maintained by InfluxData, it supports over 300 input plugins and can ship data to dozens of output targets. OxiPulse covers exactly one input (system metrics) and exactly one output (OTLP/gRPC). The comparison is not competitive — they solve different problems.

Resource usage

Telegraf's Go binary with a minimal config typically uses 30–80 MB of RAM and 0.1–0.5% CPU. That is acceptable on most servers but noticeable on constrained hardware.

OxiPulse uses under 8 MB of RAM and under 0.05% CPU in steady state. The difference matters on a $4 VPS, a Raspberry Pi, or an edge device where every megabyte counts.

Protocol support

OxiPulse Telegraf
OTLP/gRPC ✓ native ✓ via plugin
Prometheus remote write
InfluxDB line protocol ✓ native
Kafka, MQTT, AMQP
OpenTelemetry (input)

Telegraf's output breadth is unmatched. If you need to write to InfluxDB, Kafka, and an S3 bucket simultaneously, Telegraf is the right tool.

Plugin ecosystem

Telegraf's 300+ input plugins cover databases (MySQL, PostgreSQL, Redis), cloud providers (AWS CloudWatch, GCP Stackdriver), network equipment, custom scripts, and more. OxiPulse collects only CPU, RAM, disk, and network from the host OS.

If you need to correlate application metrics with system metrics in the same pipeline, Telegraf gives you that in one agent.

Offline resilience

Neither Telegraf nor most of its output plugins buffer metrics across restarts by default. OxiPulse has a built-in ring buffer that stores up to 24 hours of snapshots in memory and flushes them when the ingestor reconnects.

Auto-update

Telegraf is distributed via package managers (apt, yum). Updates require a package manager invocation or a CI pipeline. OxiPulse checks GitHub Releases 5 minutes after startup and replaces itself automatically.

When to choose Telegraf

  • You already use InfluxDB or the TICK stack
  • You need metrics from databases, message brokers, or custom scripts alongside system metrics
  • Your team is comfortable operating a more complex configuration

When to choose OxiPulse

  • You want a drop-in agent with zero configuration complexity
  • Resource footprint is a constraint
  • You use an OTLP-compatible backend (Grafana, Honeycomb, Datadog, SecuryBlack)
  • You want automatic updates and offline resilience out of the box