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Overview

This template provides a production‑ready DolphinDB instance as a Monk runnable. You can:
  • Run it directly to get a managed DolphinDB container with sensible defaults
  • Inherit it in your own runnable to seamlessly add a high-performance time-series database to your stack
DolphinDB is a high-performance distributed time-series database designed for financial and IoT data analytics. It combines in-memory computing with a columnar storage engine to deliver exceptional query performance on massive datasets. It exposes DolphinDB on port 8848, persists data to a host volume, and provides a web-based interface for database management and queries.

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What this template manages

  • DolphinDB container (configurable image tag)
  • Network service on port 8848
  • Persistent volumes for data storage

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Quick start (run directly)

  1. Load templates
monk load MANIFEST
  1. Run DolphinDB with defaults
monk run dolphindb/dolphindb
  1. Customize settings (recommended via inheritance)
Running directly uses the defaults defined in this template’s variables. Secrets added with monk secrets add will not affect this runnable unless you inherit it and reference those secrets.
  • Preferred: inherit and replace variables with secret("...") as shown below.
  • Alternative: fork/clone and edit the variables in dolphindb.yml, then monk load MANIFEST and run.
Once started, connect to localhost:8848 (or the runnable hostname inside Monk networks) to access the DolphinDB web interface.

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Configuration

Key variables you can customize in this template: 
variables:
  image_tag: "v2.00.9"    # container image tag
  db_port: "8848"         # DolphinDB service port (default: 8848)
Data is persisted under ${monk-volume-path}/dolphindb on the host. Inherit the DolphinDB runnable in your time-series application and declare a connection. Example: 
namespace: myapp
tsdb:
  defines: runnable
  inherits: dolphindb/dolphindb
analytics:
  defines: runnable
  containers:
    app:
      image: myorg/analytics
  connections:
    database:
      runnable: tsdb
      service: dolphindb
  variables:
    database-host:
      value: <- connection-hostname("database")
    database-port:
      value: "8848"
Then run your app group: 
monk run myapp/analytics

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Ports and connectivity

  • Service: dolphindb on TCP port 8848
  • From other runnables in the same process group, use connection-hostname("\<connection-name>") to resolve the DB host.

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Persistence and configuration

  • Data path: ${monk-volume-path}/dolphindb:/data
  • DolphinDB stores all databases and time-series data in this directory

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Use cases

DolphinDB excels at:
  • Financial market data analysis
  • IoT sensor data processing
  • Real-time streaming analytics
  • High-frequency trading systems
  • Time-series forecasting
  • Combine with grafana/ for time-series visualization
  • Integrate with telegraf/ for metrics collection and monitoring

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Troubleshooting

  • Ensure the host volumes are writable by the container user.
  • Check logs:
monk logs -l 500 -f dolphindb/dolphindb