Public | Automated Build

Last pushed: 6 days ago
Short Description
pipeline from a MongoDB cluster to other systems
Full Description

Mongo Connector

Docker images for the mongo-connector.

Supported tags and respective Dockerfile links

For more information about this image and its history, please see the relevant manifest file in the yeasy/docker-mongo-connector GitHub repo.

What is docker-mongo-connector?

Docker image with mongo-connector installed. The image is built based on Python 3.4.3.

How to use this image?

The docker image is auto built at

In Dockerfile

FROM yeasy/mongo-connector:latest

Local Run

By default, it will connect mongo node ($MONGO or the mongo host, on port $MONGOPORT or 27017) and elasticsearch node ($ELASTICSEARCH or the elasticsearch host, on port $ELASTICPORT or 9200).

Boot two containers with name mongo (config to cluster) and elasticsearch.

$ docker run -d --link=mongo:mongo --link=elasticsearch:elasticsearch yeasy/mongo-connector

It will connect the two containers together to sync data between each other.

Which image is based on?

The image is based on official python:3.4.3.

What has been changed?

Config TZ

Config timezone to Asia/Shanghai.

Install mongo-connector

Install the mongo-connector:2.1.

This image is officially supported on Docker version 1.7.1.

Support for older versions (down to 1.0) is provided on a best-effort basis.

User Feedback


Be sure to familiarize yourself with the repository's file before attempting a pull request.


If you have any problems with or questions about this image, please contact us through a GitHub issue.

You can also reach many of the official image maintainers via the email.


You are invited to contribute new features, fixes, or updates, large or small; we are always thrilled to receive pull requests, and do our best to process them as fast as we can.

Before you start to code, we recommend discussing your plans through a GitHub issue, especially for more ambitious contributions. This gives other contributors a chance to point you in the right direction, give you feedback on your design, and help you find out if someone else is working on the same thing.

Docker Pull Command
Source Repository