TeslaMate vs EVCC vs OVMS: Best Self-Hosted EV Monitoring Tools 2026

Electric vehicle ownership generates rich telemetry data — battery state, charging sessions, drive efficiency, location history, and more. Most manufacturers offer proprietary apps, but these come with limitations: vendor lock-in, questionable data privacy, and closed ecosystems that prevent integration with your existing smart home or energy infrastructure.

Self-hosted EV monitoring tools solve all three problems. By running your own vehicle data platform on a Raspberry Pi, home server, or VPS, you retain full ownership of every data point collected. This guide compares three leading open-source solutions: TeslaMate, EVCC, and the Open Vehicle Monitoring System (OVMS).

Why Self-Host Your EV Data

When you use a manufacturer’s native app, your driving data lives on their servers. Self-hosting gives you:

• Full data ownership — Every trip, charge session, and battery health metric stays on your hardware
• Local-first privacy — No telemetry sent to third-party analytics platforms
• Grafana dashboards — Beautiful visualizations powered by open-source dashboards, not a locked-in proprietary UI
• Smart home integration — Combine EV data with solar production, home battery, and energy consumption for optimized charging schedules
• Historical analysis — Track battery degradation over years, not months, without subscription fees

For EV owners with rooftop solar or time-of-use electricity pricing, self-hosted monitoring becomes even more valuable. You can automate charging decisions based on real-time energy production and grid pricing data.

TeslaMate: The Gold Standard for Tesla Owners

TeslaMate is the most popular self-hosted Tesla data logger, with over 7,900 GitHub stars and continuous development as of April 2026. Written in Elixir, it provides a comprehensive web interface and integrates seamlessly with Grafana for advanced dashboards.

Architecture

TeslaMate runs as a multi-container Docker stack with four services:

Docker Compose Configuration

Here is the official deployment configuration from the TeslaMate documentation:

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services:
  teslamate:
    image: teslamate/teslamate:latest
    restart: always
    environment:
      - ENCRYPTION_KEY=your-secret-encryption-key
      - DATABASE_USER=teslamate
      - DATABASE_PASS=your-secure-password
      - DATABASE_NAME=teslamate
      - DATABASE_HOST=database
      - MQTT_HOST=mosquitto
    ports:
      - 4000:4000
    volumes:
      - ./import:/opt/app/import
    cap_drop:
      - all

  database:
    image: postgres:18-trixie
    restart: always
    environment:
      - POSTGRES_USER=teslamate
      - POSTGRES_PASSWORD=your-secure-password
      - POSTGRES_DB=teslamate
    volumes:
      - teslamate-db:/var/lib/postgresql/data

  grafana:
    image: teslamate/grafana:latest
    restart: always
    environment:
      - DATABASE_USER=teslamate
      - DATABASE_PASS=your-secure-password
      - DATABASE_NAME=teslamate
      - DATABASE_HOST=database
    ports:
      - 3000:3000
    volumes:
      - teslamate-grafana-data:/var/lib/grafana

  mosquitto:
    image: eclipse-mosquitto:2
    restart: always
    command: mosquitto -c /mosquitto-no-auth.conf
    volumes:
      - mosquitto-conf:/mosquitto/config
      - mosquitto-data:/mosquitto/data

volumes:
  teslamate-db:
  teslamate-grafana-data:
  mosquitto-conf:
  mosquitto-data:

Key Features

• Sleep tracking — Monitors when your Tesla enters deep sleep and calculates vampire drain rates
• Charging analysis — Detailed charge session logs with kWh delivered, cost estimates, and charging curves
• Drive statistics — Efficiency per trip, energy consumption by temperature, and elevation impact analysis
• Location history — GPS track logging with geofencing support for automatic charge/drive categorization
• Battery health — Long-term degradation tracking via capacity estimation over thousands of charge cycles
• Import/export — CSV import for migrating from other tools; export for backup and analysis

Resource Requirements

TeslaMate is relatively lightweight but requires PostgreSQL and Grafana. A Raspberry Pi 4 with 4 GB RAM or any x86 machine with 2 GB RAM runs it comfortably. The PostgreSQL database grows at roughly 10-50 MB per month depending on driving frequency.

EVCC: Smart Charging with Solar Integration

EVCC takes a different approach. Rather than logging historical data, EVCC focuses on intelligent charging control — optimizing when and how fast your EV charges based on solar production, grid prices, and battery state. With over 6,400 GitHub stars, it has become the go-to tool for solar-powered EV charging in Europe and beyond.

Written in Go, EVCC is a single binary that handles multiple EV brands, charger protocols, and energy sources.

Supported Hardware

EVCC works with a broad range of hardware:

Configuration

EVCC uses a YAML configuration file. Here is a minimal example that ties solar production to EV charging:

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site:
  - title: Home
    meters:
      grid: grid_meter
      pv:
        - solar_inverter
      battery:
        - home_battery

meters:
  - name: grid_meter
    type: modbus
    id: 1
    uri: rs485.tcp.local:502
    power: Power

  - name: solar_inverter
    type: sunnyboy
    uri: http://sma-inverter.local

chargers:
  - name: wallbox
    type: easee
    user: your-email@example.com
    password: your-password

vehicles:
  - name: ev
    type: tesla
    title: My Tesla
    user: your-tesla-email
    password: your-tesla-password
    mode: pv       # charge only with surplus solar
    minCurrent: 6  # minimum charging current in amps
    maxCurrent: 16 # maximum charging current in amps

Running EVCC with Docker

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docker run -d \
  --name evcc \
  -p 7070:7070 \
  -v /opt/evcc:/root/.evcc \
  --restart unless-stopped \
  evcc/evcc:latest

Key Features

• PV (photovoltaic) mode — Charges your EV using only excess solar production; automatically throttles charging current as solar output fluctuates
• Grid price awareness — Integrates with electricity price APIs to schedule charging during off-peak hours
• Multi-vehicle support — Manage multiple EVs with different charging priorities and schedules
• Battery management — Integrates with home battery systems (Powerwall, Sungrow, BYD) to coordinate EV and home energy storage
• MQTT integration — Publishes charging state and power data for use with Home Assistant, Node-RED, or custom automation
• Web UI — Real-time dashboard showing solar production, grid import/export, battery state, and charging progress
• API — REST API for programmatic control of charging sessions

Resource Requirements

EVCC is a single Go binary and runs comfortably on a Raspberry Pi Zero W. Typical memory usage is under 50 MB. No database is required — configuration is stored in a single YAML file.

OVMS: Multi-Brand Vehicle Monitoring

The Open Vehicle Monitoring System (OVMS) is the most hardware-agnostic option. Originally built for the Think City electric car, OVMS v3 now supports Renault Zoe, Nissan Leaf, Mitsubishi Outlander PHEV, Hyundai Kona Electric, Jaguar I-PACE, and many others through community-developed vehicle modules.

OVMS uses a hardware module (typically an ESP32-based device connected to the vehicle’s OBD-II port) that communicates with a self-hosted server. This architecture means it works even with vehicles that lack built-in telematics APIs.

Architecture

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[OBD-II Port] → [ESP32 OVMS Module] → [WiFi/Cellular] → [OVMS Server] → [Web UI / Mobile App]

Server Deployment

The OVMS server requires MongoDB and can be deployed with Docker:

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services:
  ovms-server:
    image: openvehicles/ovms-server:latest
    restart: always
    ports:
      - 6865:6865  # Vehicle module communication
      - 6866:6866  # Client API
      - 80:80      # Web interface
    environment:
      - OVMS_MONGO_HOST=mongodb
      - OVMS_MONGO_DB=ovms
      - OVMS_MONGO_USER=ovms
      - OVMS_MONGO_PASS=your-mongo-password

  mongodb:
    image: mongo:7
    restart: always
    environment:
      - MONGO_INITDB_ROOT_USERNAME=admin
      - MONGO_INITDB_ROOT_PASSWORD=your-admin-password
      - MONGO_INITDB_DATABASE=ovms
    volumes:
      - ovms-mongo-data:/data/db

volumes:
  ovms-mongo-data:

Key Features

• Hardware-based monitoring — Works with vehicles that don’t expose a cloud API
• Community modules — 20+ vehicle-specific modules developed by the community
• Real-time alerts — Push notifications for charge complete, low battery, vehicle movement, and temperature extremes
• Location tracking — GPS position with trip history and geofencing
• Remote commands — Lock/unlock, start/stop climate control, and charging control (vehicle-dependent)
• Open protocol — The OVMS protocol is documented and can be integrated with custom applications
• Mobile apps — Official Android and iOS apps for remote monitoring and control

Hardware Requirements

Unlike TeslaMate and EVCC, OVMS requires a hardware module ($30-60 for an ESP32 dev board plus a compatible OBD-II adapter). This is both a strength (works without manufacturer API access) and a limitation (requires physical installation).

Resource Requirements

The OVMS server is lightweight — the Go-based server binary uses under 100 MB RAM. MongoDB requires 512 MB minimum. A Raspberry Pi 4 with 2 GB RAM is sufficient for a single-vehicle deployment.

Comparison Table

Which Should You Choose?

Choose TeslaMate If:

• You own a Tesla (Model 3, Y, S, or X)
• You want comprehensive historical data and beautiful Grafana dashboards
• You care about battery health tracking and long-term degradation analysis
• You want the most mature and well-documented option

Choose EVCC If:

• You have solar panels and want to charge your EV with surplus energy
• You have dynamic electricity pricing and want to optimize charging costs
• You want to manage multiple EVs and chargers from a single platform
• You need integration with home battery systems and smart meters

Choose OVMS If:

• You drive a non-Tesla EV that lacks a reliable cloud API
• You want a hardware-based solution that doesn’t depend on manufacturer servers
• You need vehicle-specific modules for older or niche EV models
• You want native mobile apps for iOS and Android

Combining Tools

These tools are not mutually exclusive. A common setup among self-hosting enthusiasts:

• TeslaMate for historical data logging and Grafana dashboards
• EVCC for intelligent charging control based on solar production
• Both communicate via MQTT to a central Home Assistant instance

The OVMS server can also be combined with EVCC — OVMS provides vehicle telemetry while EVCC handles charging optimization, bridged through MQTT messages.

Deployment on a Raspberry Pi

All three tools run on a Raspberry Pi 4 (4 GB RAM recommended). Here is a quick-start for the most popular option:

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# Install Docker and Docker Compose
curl -fsSL https://get.docker.com -o get-docker.sh
sudo sh get-docker.sh
sudo usermod -aG docker $USER

# Create TeslaMate directory
mkdir ~/teslamate && cd ~/teslamate

# Create docker-compose.yml (use the config from above)
nano docker-compose.yml

# Set your secure passwords before starting
# Replace 'your-secret-encryption-key' and 'your-secure-password'

# Start all services
docker compose up -d

# Access the web UI
# TeslaMate: http://<raspberry-pi-ip>:4000
# Grafana:   http://<raspberry-pi-ip>:3000 (admin/admin)

For EVCC on the same Pi:

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mkdir ~/evcc && cd ~/evcc
docker run -d \
  --name evcc \
  -p 7070:7070 \
  -v $(pwd)/evcc.yaml:/root/.evcc/evcc.yaml \
  --restart unless-stopped \
  evcc/evcc:latest

# Access EVCC UI at http://<raspberry-pi-ip>:7070

FAQ

Can TeslaMate and EVCC run on the same server?

Yes. Both are Docker-based and can coexist on the same machine. TeslaMate uses ports 4000 and 3000, while EVCC uses port 7070. A Raspberry Pi 4 with 4 GB RAM handles both simultaneously. Many users run TeslaMate for data logging alongside EVCC for charging control.

Does OVMS work with Tesla vehicles?

OVMS has limited Tesla support through the vehicle’s CAN bus, but TeslaMate is significantly better for Tesla-specific data. OVMS excels with vehicles like the Renault Zoe, Nissan Leaf, and Mitsubishi Outlander PHEV where manufacturer APIs are limited or nonexistent.

Do I need a static IP or domain name?

For local-only access, no — just use your server’s local IP address. For remote access, consider using a reverse proxy with TLS (such as Traefik or Caddy) or a VPN tunnel. Never expose these services directly to the internet without authentication.

How much storage does TeslaMate’s database require?

PostgreSQL storage grows at approximately 10-50 MB per month depending on how frequently you drive. After one year of daily driving, expect 200-600 MB. With a 64 GB SD card or SSD, you have years of data before storage becomes a concern.

Can EVCC control non-EV devices like heat pumps or water heaters?

Yes. EVCC supports generic load points through its sma, shelly, and tasmota meter types. You can configure it to divert excess solar to a water heater, heat pump, or any smart plug that supports the configured protocol.

Is there a cost to self-host these tools?

All three are completely free and open-source. Hardware costs are minimal: a Raspberry Pi 4 ($35-75) for TeslaMate or EVCC, plus an ESP32 module ($10-30) for OVMS. Compare this to manufacturer telematics subscriptions that can cost $100-300 per year.

How secure is self-hosted EV data?

Self-hosting is more secure than cloud-based alternatives because your data never leaves your network. Use strong passwords for database and API access, keep Docker images updated, and use a reverse proxy with TLS for remote access. TeslaMate’s ENCRYPTION_KEY setting encrypts your Tesla API tokens at rest.

For related reading, see our HertzBeat vs Prometheus vs Netdata monitoring comparison for broader infrastructure monitoring options, the Grafana Pyroscope continuous profiling guide if you want to extend Grafana beyond EV dashboards, and our smart home bridges comparison for integrating EV data with home automation.