Deploy

Deployment Models

Example dataflow between Cosmos DB and MongoDB

Single binary

Dsync will run wherever there's CPU and RAM. This can be a laptop, VM or a docker container.

You can install dsync with any of the following methods:

• Run as a docker container: docker run markadiom/dsync

• Build from the source

• Download the latest release in GitHub.

Azure users can also leverage marketplace offerings for Azure DocumentDB , Cosmos DB NoSQL and other migrations.

You can use Homebrew to easily install Dsync on your Mac:

brew install adiom-data/homebrew-tap/dsync

Multi-worker

For large migrations where vertical scaling of dsync VM isn't feasible, and for data platforms requiring on-demand data mobility and continuous data replication, we support a horizontally scalable deployment of dsync with external Coordinator. Read more about it here: Scalable Deployment

Azure users can leverage marketplace offering: https://marketplace.microsoft.com/en-us/product/container/adiom.adiom_dsync_container. Read more about it in Azure Marketplace.

Infrastructure Requirements

Dsync doesn't store any in-transit data on-disk (only logs). As such CPU, RAM and network bandwidth are the core requirements.

For small scale testing and development, 1 or 2 CPU with 2GB RAM is more than sufficient. For larger use cases, we recommend dedicating 4 CPU and 16 GB RAM, or 8 CPU and 32 GB RAM for a dsync instance, whether running as a single binary or in a multi-worker configuration.

However Dsync is deployed, it must have direct network access to both the source and the destination.