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ScriptsApr 11, 2026·3 min de lectura

InfluxDB — Scalable Time Series Datastore for Metrics & Events

InfluxDB is a scalable time series database for metrics, events, and real-time analytics. InfluxDB 3.0 is a complete rewrite in Rust with columnar Apache Arrow storage, SQL and InfluxQL queries, and unlimited cardinality.

Introducción

InfluxDB is a scalable time series database for metrics, events, and real-time analytics. InfluxDB 3.0 is a complete rewrite in Rust built on Apache Arrow columnar storage (via DataFusion), providing unlimited cardinality, SQL support, and much better analytics performance than v1/v2. Used by Cisco, eBay, IBM, and countless IoT deployments.

What InfluxDB Does

  • Time series storage — optimized for time-ordered data
  • High write throughput — millions of points per second
  • Downsampling — continuous queries / tasks to roll up data
  • Retention policies — auto-delete old data
  • SQL + InfluxQL + Flux — multiple query languages
  • Apache Arrow/Parquet — columnar storage in v3
  • Unlimited cardinality — v3 removes series cardinality limits
  • Telegraf — 200+ plugins for data collection
  • Kapacitor — alerting and stream processing
  • Grafana integration — first-class data source

Architecture

InfluxDB 3.0 architecture:

  • Write — line protocol to WAL, flushed to Parquet files
  • Query — DataFusion execution engine on Parquet + in-memory WAL
  • Storage — object storage (S3, local disk) for Parquet
  • Compactor — merges small Parquet files into larger ones

Self-Hosting

# docker-compose.yml
version: "3"
services:
  influxdb:
    image: influxdb:3-core
    ports: ["8086:8086"]
    volumes: ["influx-data:/var/lib/influxdb3"]
    environment:
      INFLUXDB3_NODE_IDENTIFIER_PREFIX: "node-1"
      INFLUXDB3_OBJECT_STORE: "file"
      INFLUXDB3_DB_DIR: "/var/lib/influxdb3"
volumes:
  influx-data:

Key Features

  • Purpose-built for time series
  • v3 built on Apache Arrow/Parquet
  • SQL and InfluxQL query
  • Unlimited cardinality (v3)
  • High ingest throughput
  • Downsampling and retention
  • Telegraf ecosystem (200+ plugins)
  • Grafana integration
  • Cloud-native managed offering

Comparison

Database Model Storage SQL
InfluxDB v3 Time series Parquet + Arrow Yes + InfluxQL
TimescaleDB Postgres extension Postgres Native
Prometheus Time series Local TSDB PromQL only
VictoriaMetrics Time series Custom MetricsQL
QuestDB Time series Columnar SQL
ClickHouse OLAP Columnar SQL

FAQ

Q: v2 vs v3 differences? A: v3 is a complete rewrite (Rust + Apache Arrow/DataFusion), supporting SQL, with no cardinality limits and storage placed on object storage. v2 uses Go + the TSM engine and has cardinality issues.

Q: How do I choose between this and Prometheus? A: Prometheus is better for monitoring (pull model, simple deployment); InfluxDB is better for general-purpose time series data (push model, SQL queries, longer retention).

Q: Does it support PromQL? A: v3 has experimental PromQL support, aiming to be a Prometheus alternative.

Sources

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