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How Automerge works

This document explains how Automerge stores data internally. You shouldn't need to read it in order to use Automerge in your application, but you might find it useful if you want to hack on the Automerge code itself.

Document, changes, and operations

You get an Automerge instance by calling Automerge.init() (creates a new, empty document) or Automerge.load() (loads an existing document, typically from a file on disk). By default, this document exists only in memory on a single device, and you don't need any network communication for read or write access. There may be a separate networking layer that asynchronously propagates changes from one device to another, but that networking layer is outside of the scope of Automerge itself.

The Automerge instance represents the current state of your application (or some part of it). The state is immutable and is never updated in place. Instead, whenever you want to do something that changes the state, you call a function that takes the old state as first argument, and returns a new state reflecting the change. There are two ways how the state can change:

  1. Local changes, which are generally triggered by the user changing some piece of application data in the user interface. Such editing by the user is expressed by calling Automerge.change(), which groups together a block of operations that should be applied as an atomic unit. Within the change callback you have access to a mutable version of the Automerge document, implemented as a Proxy). The proxy records any mutations you make as operations (e.g. changing the value of a particular property of a particular object). The change() function returns a new copy of the state with those operations applied.
  2. Remote changes: a user on another device has edited their copy of a document, that change was sent to you via the network, and now you want to apply it to your own copy of the document. Remote operations are applied using Automerge.applyChanges(), which again returns a new copy of the state. For testing purposes there is also Automerge.merge(), which is is a short-cut for the case where the "remote" document is actually just another instance of Automerge in the same process.

Some terminology:

  • An operation is a fine-grained description of a single modification, e.g. setting the value of a particular property of a particular object, or inserting one element into a list. Users normally never see operations โ€” they are a low-level implementation detail.
  • A change is a collection of operations grouped into a unit that is applied atomically (a bit like a database transaction). Each call to Automerge.change() produces exactly one change, and inside the change there may be any number of operations. A change is also the smallest unit that gets transmitted over the network to other devices.
  • A document is the state of a single Automerge instance. The state of a document is determined by the set of all changes that have been applied to it. Automerge ensures that whenever any two documents have seen the same set of changes, even if the changes were applied in a different order, then those documents are in the same state. This means an Automerge document is a CRDT.

Automerge.getChanges() returns all the changes that have occurred between one document state and another, so that they can be encoded and sent over the network to other devices. On the recipient's end, Automerge.applyChanges() updates the corresponding document to incorporate those changes.

You can save a document to disk using This function returns a byte array in which the state of the document has been encoded in a compressed form. Conversely, Automerge.load() decodes that byte array and returns an instance of the document. You can store this byte array in whatever way works best on your platform, e.g. as a file on the filesystem, or in IndexedDB in a web browser. The saved document state actually contains the entire change history of the document (a bit like a Git repository), but the compression makes this efficient.

One day, we may need to allow this history to be pruned in order to save disk space. There are also privacy implications in storing the whole history: any new collaborator who gets access to a document can see all past states of the document, including any content that is now deleted. However, for now we are choosing to preserve all history as it makes synchronisation easier (imagine a device that has been offline for a long time, and then needs to catch up on everything that has been changed by other users while it was offline). Moreover, being able to inspect edit history is itself a useful feature.

Actor IDs and dependencies

Each Automerge instance has an actor ID โ€” a UUID that is generated randomly whenever you do Automerge.init() or Automerge.load() (unless you explicitly pass an actor ID into those functions). Whenever you make a local edit on that Automerge instance, the operations are tagged with that actor ID as the origin. All changes made on a Automerge instance are numbered sequentially, starting with 1 and never skipping or reusing sequence numbers. We assume that nobody else is using the same actor ID, and thus each change is uniquely identified by the combination of its originating actor ID and its sequence number. That unique identifier for the change always remains fixed, even when it is applied on remote copies of the document.

An actor ID is a bit similar to a device ID. Each device can generate changes independently from every other device, and so each device needs to have its own numbering sequence. You can have several actor IDs for the same device, for example if the user might run several instances of the application on the same device (in which case, each instance needs its own actor ID). However, there is a performance cost to having lots of actor IDs, so it's a good idea to keep using the same actor ID if possible (at least for the lifetime of an application process).

When you make several changes to a document over time, later changes may depend on earlier ones. For example, an earlier change may create a list object, and a later change may insert an item into that list. To track those changes, each change contains the SHA-256 hashes of the changes it depends on (similarly to how a Git commit contains the hashes of the previous commit).

In a sequential editing history, each change contains has only one dependency hash. But if several users are working concurrently (perhaps even working offline), the hash graph may contain branches and merges. A merge occurs when there is a change that has more than one dependency, similarly to a merge commit in Git.

When we send changes from one device to another, we apply the changes in the order specified by the dependencies between them. Automerge.applyChanges() performs this ordering automatically. If two changes appear in parallel branches, we call them concurrent, and they may be applied in either order.