Instant uses a Firebase-inspired interface for mutations. We call our mutation language InstaML

Why InstaML

We love Firebase's simple mutation API and how it provides optimistic updates and rollbacks for free. We wanted to bring the same experience with support for relations.

You can try out the examples below with this sandbox.


transact is used for committing transaction chunks. transact takes only one parameter, an array of tx transaction chunks. For example running the following

  tx.todos["workout"].update({title: "Go on a run"}),
  tx.todos["protein"].update({title: "Drink protein"}),
  tx.todos["sleep"].update({title: "Go to bed early"}),
  tx.todos["standup"].update({title: "Do standup"}),
  tx.todos["reviewPRs"].update({title: "Review PRs"}),
  tx.todos["focus"].update({title: "Code a bunch"}),
  tx.goals["health"].update({title: "Get fit!"})
    .link({ todos: "workout"})
    .link({ todos: "protein"})
    .link({ todos: "sleep"})
  tx.goals["work"].update({title: "Get promoted!"})
    .link({ todos: "standup"})
    .link({ todos: "reviewPRs"})
    .link({ todos: "focus"})

Will generate:

  • todos, identified as workout, protein, sleep, standup, reviewPRs, and focus
  • goals, identified as health and work
  • todos workout, protein, and sleep are associated with goal health
  • todos standup, reviewPRs, and focus are associated with goal work


tx is a proxy object which creates transaction chunks to be commited via transact. It follows the format

  • NAMESPACE_LABEL refers to the namespace to commit (e.g. goals, todos)
  • GLOBAL_UNIQUE_IDENTIFER is the id to look up in the namespace. This id must be unique across all namespaces. Suppose we have a namespace authors, and editors. If we have id joe in authors, we cannot have id joe in editors as well.
  • ACTION is one of update, delete, link, unlink
  • ACTION_SPECIFIC_DATA depends on the action
    • update takes in an object of information to commit
    • delete is the only aciton that doesn't take in any data,
    • link and unlink takes an object of label-entity pairs to create/delete associations


We use the update action to create entities.

transact([tx.goals[id()].update({ title: 'eat' })])

This creates a new goal with the following properties:

  • It's identified by a randomly generated id via the id() function.
  • It has an attribute title with value eat.

Similar to NoSQL, you don't need to use the same schema for each entity in a namespace. After creating the previous goal you can run the following:

    priority: 'none',
    isSecret: true,
    value: 10,
    aList: [1, 2, 3],
    anObject: { foo: 'bar' },

You can store strings, numbers, booleans, arrays, and objects as values. You can also generate values via functions. Below is an example for picking a random goal title.

    title: ['eat', 'sleep', 'hack', 'repeat'][Math.floor(Math.random() * 4)],

The update action is also used for updating entities. Suppose we had created the following goal

  tx.goals['eat'].update({ priority: 'top', lastTimeEaten: 'Yesterday' }),

We eat some food and decide to update the goal. We can do that like so:

transact([tx.goals['eat'].update({ lastTimeEaten: 'Today' })])

This will only update the value of the lastTimeEaten attribute for entity eat.

In the previous example we used eat as the identifer for illustrating how to update an entity. In practice though you will likely want to generate unique and random string identifiers for your entities via the id() function.

This is because ids must be unique across all namespaces. In a real application, ids like eat, joe or stopa are unlikely to be unique and may result in unexpected behavior if the same identifier appears in more than one namespace.


The delete action is used for deleting entities.


You can generate an array of delete txs to delete all entities in a namespace

const { goals } = useQuery({goals: {}}
transact(goals.map(g => tx.goals[g.id].delete()));

Calling delete on an entity also deletes its associations. So no need to worry about cleaning up previously created links.

link is used to create associations.

Suppose we create a goal and a todo.

  tx.todos['workout'].update({ title: 'Go on a run' }),
  tx.goals['health'].update({ title: 'Get fit!' }),

We can associate health with workout like so:

transact([tx.goals['health'].link({ todos: 'workout' })])

We could have done all this in one transact too via chaining transaction chunks.

  tx.todos['workout'].update({ title: 'Go on a run' }),
  tx.goals['health'].update({ title: 'Get fit!' }).link({ todos: 'workout' }),

You can chain multiple links in one tx too.

  tx.todos['workout'].update({ title: 'Go on a run' }),
  tx.todos['protein'].update({ title: 'Drink protein' }),
  tx.todos['sleep'].update({ title: 'Go to bed early' }),
    .update({ title: 'Get fit!' })
    .link({ todos: 'workout' })
    .link({ todos: 'protein' })
    .link({ todos: 'sleep' }),

Order matters when creating links.

transact([tx.goals['health'].link({ todos: 'workout' })])

This creates:

  • A forward link from entity health to entity workout via goals -> todos
  • A reverse link from entity workout to entity health via todos -> _goals

We can query associations in both directions via these links

const { goals, todos } = useQuery({
  goals: { todos: {} },
  todos: { _goals: {} },

Link labels do not need to match the namespace of the right-side entity. We could have done this instead:

transact([tx.goals['health'].link({ priorities: 'workout' })])

This creates:

  • A forward link from entity health to entity workout via goals -> priorities
  • A reverse link from entity workout to entity health via todos -> _goals through priorities

In this case the getting the forward associations is the same as before,but reverse association requires the through key.

const { goals, todos } = useQuery({
  goals: { todos: {} },
  todos: { _goals: { $: { through: 'priorities' } } },

Using different link labels is useful for disambiguation. Consider the following:

  tx.users['joe'].update({ name: 'Joe' }),
  tx.users['stopa'].update({ name: 'Stopa' }),
    .update({ title: 'Graph Based Firebase' })
    .link({ author: 'stopa' })
    .link({ editor: 'joe' }),

Here we have:

  • users, identified as joe and stopa
  • A post, identified as essay which was authored by user stopa and edited by user joe.

Although joe and stopa are both entities in the users namespace, the context between posts and users is different for these associations. Being able to assign a different link label enables us to differentiate between authors, editors, authored posts, and edited posts at query time.

const query = {
  "posts": {
    "author": {},
    "editor": {}
  "users": {
    "authoredPosts": {
      "$": {
        "through": "author",
        "is": "_posts"
    "editedPosts": {
      "$": {
        "through": "editor",
        "is": "_posts"

Links can be removed via unlink

transact([tx.goals['health'].unlink({ todos: 'workout' })])

This removes both:

  • The forward link from entity health to entity workout
  • The reverse link from entity workout to entity health

Similar to other actions, we can chain multiple unlink on a tx.

    .unlink({ todos: 'workout' })
    .unlink({ todos: 'protein' })
    .unlink({ todos: 'sleep' }),
    .unlink({ todos: 'standup' })
    .unlink({ todos: 'reviewPRs' })
    .unlink({ todos: 'focus' }),

Although unlink will remove links in both directions, it only accepts the forward link as an input. So this works:

transact([tx.goals['health'].unlink({ todos: 'workout' })])

But this does not

transact([tx.todos['workout'].unlink({ _goals: 'health' })])