The reactive data store for local-first apps.
Creating a Store requires just a simple call to the createStore function. Once you have one, you can easily set Values in it by unique Id. And of course you can easily get them back out again.
Read more about using keyed value data in The Basics guide.
const store = createStore()
.setValues({employees: 3})
.setValue('open', true);
console.log(store.getValues());
// -> {employees: 3, open: true}Level up to use tabular data.
For other types of data applications, a tabular data structure is more useful. TinyBase lets you set and get nested Table, Row, or Cell data, by unique Id - and in the same Store as the keyed values!
Read more about setting and changing data in The Basics guide.
store
.setTable('pets', {fido: {species: 'dog'}})
.setCell('pets', 'fido', 'color', 'brown');
console.log(store.getRow('pets', 'fido'));
// -> {species: 'dog', color: 'brown'}Register granular listeners.
The magic starts to happen when you register listeners on a Value, Table, Row, or Cell. They get called when any part of that object changes. You can also use wildcards - useful when you don't know the Id of the objects that might change.
Read more about listeners in the Listening To Stores guide.
const listenerId = store.addTableListener('pets', () =>
console.log('changed'),
);
store.setCell('pets', 'fido', 'sold', false);
// -> 'changed'
store.delListener(listenerId);Call hooks to bind to data.
If you're using React in your application, the optional ui-react module provides hooks to bind to the data in a Store.
More magic! The useCell hook in this example fetches the dog's color. But it also registers a listener on that cell that will fire and re-render the component whenever the value changes.
Basically you simply describe what data you want in your user interface and TinyBase will take care of the whole lifecycle of updating it for you.
Read more about the using hooks in the Using React Hooks guide.
const App1 = () => {
const color = useCell('pets', 'fido', 'color', store);
return <>Color: {color}</>;
};
const app = document.createElement('div');
const root = ReactDOMClient.createRoot(app);
root.render(<App1 />);
console.log(app.innerHTML);
// -> 'Color: brown'
store.setCell('pets', 'fido', 'color', 'walnut');
console.log(app.innerHTML);
// -> 'Color: walnut'Pre-built reactive components.
By default, a Store can contain any arbitrary Value, and a Row can contain any arbitrary Cell. But you can add a ValuesSchema or a TablesSchema to a Store to ensure that the values are always what you expect: constraining their types, and providing defaults.
In this example, we set a new Row without the sold Cell in it. The schema ensures it's present with default of false.
Read more about schemas in the Using Schemas guide.
store.setTablesSchema({
pets: {
species: {type: 'string'},
color: {type: 'string'},
sold: {type: 'boolean', default: false},
},
});
store.setRow('pets', 'polly', {species: 'parrot'});
console.log(store.getRow('pets', 'polly'));
// -> {species: 'parrot', sold: false}
store.delTablesSchema();Persist to storage, SQLite, CRDTs.
You can easily persist a Store between browser page reloads or sessions. You can also synchronize it with a web endpoint, or (if you're using TinyBase in an appropriate environment), load and save it to a file. New in v4.0, you can bind TinyBase to SQLite via a range of modules, or to Yjs or Automerge CRDT documents.
Read more about persisters in the Persisting Data guide.
const persister = createSessionPersister(store, 'demo');
await persister.save();
console.log(sessionStorage.getItem('demo'));
// ->
`
[
{
"pets":{
"fido":{"species":"dog","color":"walnut","sold":false},
"polly":{"species":"parrot","sold":false}
}
},
{"employees":3,"open":true}
]
`;
persister.destroy();
sessionStorage.clear();Build complex queries with TinyQL.
The Queries object lets you query data across tables, with filtering and aggregation - using a SQL-adjacent syntax called TinyQL.
Accessors and listeners let you sort and paginate the results efficiently, making building rich tabular interfaces easier than ever.
In this example, we have two tables: of pets and their owners. They are joined together by the pet's ownerId Cell. We select the pet's species, and the owner's state, and then aggregate the prices for the combinations.
We access the results by descending price, essentially answering the question: "which is the highest-priced species, and in which state?"
Needless to say, the results are reactive too! You can add listeners to queries just as easily as you do to raw tables.
Read more about Queries in the v2.0 Release Notes, the Making Queries guide, and the Car Analysis demo and Movie Database demo.
store
.setTable('pets', {
fido: {species: 'dog', ownerId: '1', price: 5},
rex: {species: 'dog', ownerId: '2', price: 4},
felix: {species: 'cat', ownerId: '2', price: 3},
cujo: {species: 'dog', ownerId: '3', price: 4},
})
.setTable('owners', {
1: {name: 'Alice', state: 'CA'},
2: {name: 'Bob', state: 'CA'},
3: {name: 'Carol', state: 'WA'},
});
const queries = createQueries(store);
queries.setQueryDefinition(
'prices',
'pets',
({select, join, group}) => {
select('species');
select('owners', 'state');
select('price');
join('owners', 'ownerId');
group('price', 'avg').as('avgPrice');
},
);
queries
.getResultSortedRowIds('prices', 'avgPrice', true)
.forEach((rowId) => {
console.log(queries.getResultRow('prices', rowId));
});
// -> {species: 'dog', state: 'CA', avgPrice: 4.5}
// -> {species: 'dog', state: 'WA', avgPrice: 4}
// -> {species: 'cat', state: 'CA', avgPrice: 3}
queries.destroy();Define metrics and aggregations.
A Metrics object makes it easy to keep a running aggregation of Cell values in each Row of a Table. This is useful for counting rows, but also supports averages, ranges of values, or arbitrary aggregations.
In this example, we create a new table of the pet species, and keep a track of which is most expensive. When we add horses to our pet store, the listener detects that the highest price has changed.
Read more about Metrics in the Using Metrics guide.
store.setTable('species', {
dog: {price: 5},
cat: {price: 4},
worm: {price: 1},
});
const metrics = createMetrics(store);
metrics.setMetricDefinition(
'highestPrice', // metricId
'species', // tableId to aggregate
'max', // aggregation
'price', // cellId to aggregate
);
console.log(metrics.getMetric('highestPrice'));
// -> 5
metrics.addMetricListener('highestPrice', () =>
console.log(metrics.getMetric('highestPrice')),
);
store.setCell('species', 'horse', 'price', 20);
// -> 20
metrics.destroy();Create indexes for fast lookups.
An Indexes object makes it easy to look up all the Row objects that have a certain value in a Cell.
In this example, we create an index on the species Cell values. We can then get the the list of distinct Cell value present for that index (known as 'slices'), and the set of Row objects that match each value.
Indexes objects are reactive too. So you can set listeners on them just as you do for the data in the underlying Store.
Read more about Indexes in the Using Indexes guide.
const indexes = createIndexes(store);
indexes.setIndexDefinition(
'bySpecies', // indexId
'pets', // tableId to index
'species', // cellId to index
);
console.log(indexes.getSliceIds('bySpecies'));
// -> ['dog', 'cat']
console.log(indexes.getSliceRowIds('bySpecies', 'dog'));
// -> ['fido', 'rex', 'cujo']
indexes.addSliceIdsListener('bySpecies', () =>
console.log(indexes.getSliceIds('bySpecies')),
);
store.setRow('pets', 'lowly', {species: 'worm'});
// -> ['dog', 'cat', 'worm']
indexes.destroy();Model table relationships.
A Relationships object lets you associate a Row in a local Table with the Id of a Row in a remote Table. You can also reference a table to itself to create linked lists.
In this example, the species Cell of the pets Table is used to create a relationship to the species Table, so that we can access the price of a given pet.
Like everything else, you can set listeners on Relationships too.
Read more about Relationships in the Using Relationships guide.
const relationships = createRelationships(store);
relationships.setRelationshipDefinition(
'petSpecies', // relationshipId
'pets', // local tableId to link from
'species', // remote tableId to link to
'species', // cellId containing remote key
);
console.log(
store.getCell(
relationships.getRemoteTableId('petSpecies'),
relationships.getRemoteRowId('petSpecies', 'fido'),
'price',
),
);
// -> 5
relationships.destroy();Set checkpoints for an undo stack.
A Checkpoints object lets you set checkpoints on a Store. Move forward and backward through them to create undo and redo functions.
In this example, we set a checkpoint, then sell one of the pets. Later, the pet is brought back to the shop, and we go back to that checkpoint to revert the store to its previous state.
Read more about Checkpoints in the Using Checkpoints guide.
const checkpoints = createCheckpoints(store);
store.setCell('pets', 'felix', 'sold', false);
checkpoints.addCheckpoint('pre-sale');
store.setCell('pets', 'felix', 'sold', true);
console.log(store.getCell('pets', 'felix', 'sold'));
// -> true
checkpoints.goBackward();
console.log(store.getCell('pets', 'felix', 'sold'));
// -> falseType definitions & ORM-like APIs
TinyBase has comprehensive type definitions, and even offers definitions that infer API types from the data schemas you apply.
Furthermore, you can easily create TypeScript .d.ts definitions that model your data and encourage type-safety when reading and writing data - as well as .ts implementations that provide ORM-like methods for your named tables.
Read more about type support in the TinyBase and TypeScript guide.
const tools = createTools(store);
const [dTs, ts] = tools.getStoreApi('shop');
// -- shop.d.ts --
/* Represents the 'pets' Table. */
export type PetsTable = {[rowId: Id]: PetsRow};
/* Represents a Row when getting the content of the 'pets' Table. */
export type PetsRow = {species: string /* ... */};
//...
// -- shop.ts --
export const createShop: typeof createShopDecl = () => {
//...
};Did we say tiny?
