DB Core/live Queries

Live Queries

This skill builds on db-core.

TanStack DB live queries use a SQL-like fluent query builder to create reactive derived collections that automatically update when underlying data changes. The query engine compiles queries into incremental view maintenance (IVM) pipelines using differential dataflow (d2ts), so only deltas are recomputed.

All operators, string functions, math functions, and aggregates are incrementally maintained. Prefer them over equivalent JS code.

Setup

Minimal example using the core API (no framework hooks):

import {
  createCollection,
  createLiveQueryCollection,
  liveQueryCollectionOptions,
  eq,
} from '@tanstack/db'

// Assume usersCollection is already created via createCollection(...)

// Option 1: createLiveQueryCollection shorthand
const activeUsers = createLiveQueryCollection((q) =>
  q
    .from({ user: usersCollection })
    .where(({ user }) => eq(user.active, true))
    .select(({ user }) => ({
      id: user.id,
      name: user.name,
      email: user.email,
    })),
)

// Option 2: full options via liveQueryCollectionOptions
const activeUsers2 = createCollection(
  liveQueryCollectionOptions({
    query: (q) =>
      q
        .from({ user: usersCollection })
        .where(({ user }) => eq(user.active, true))
        .select(({ user }) => ({
          id: user.id,
          name: user.name,
        })),
    getKey: (user) => user.id,
  }),
)

// The result is a live collection -- iterate, subscribe, or use as source
for (const user of activeUsers) {
  console.log(user.name)
}

Core Patterns

1. Filtering with where + operators

Chain .where() calls (ANDed together) using expression operators. Use and(), or(), not() for complex logic.

import { eq, gt, or, and, not, inArray, like } from '@tanstack/db'

const results = createLiveQueryCollection((q) =>
  q
    .from({ user: usersCollection })
    .where(({ user }) => eq(user.active, true))
    .where(({ user }) =>
      and(
        gt(user.age, 18),
        or(eq(user.role, 'admin'), eq(user.role, 'moderator')),
        not(inArray(user.id, bannedIds)),
      ),
    ),
)

Boolean column references work directly:

.where(({ user }) => user.active)        // bare boolean ref
.where(({ user }) => not(user.suspended)) // negated boolean ref

Comparisons follow PostgreSQL semantics. Comparisons involving null or undefined are unknown and do not match; use isNull() or isUndefined(). NaN (and an invalid Date) equals itself and sorts after every other non-null value.

2. Joining two collections

Join conditions must use eq() (equality only -- IVM constraint). Default join type is left. Convenience methods: leftJoin, rightJoin, innerJoin, fullJoin.

import { eq } from '@tanstack/db'

const userPosts = createLiveQueryCollection((q) =>
  q
    .from({ user: usersCollection })
    .innerJoin({ post: postsCollection }, ({ user, post }) =>
      eq(user.id, post.userId),
    )
    .select(({ user, post }) => ({
      userName: user.name,
      postTitle: post.title,
    })),
)

Multiple joins:

q.from({ user: usersCollection })
  .join({ post: postsCollection }, ({ user, post }) => eq(user.id, post.userId))
  .join({ comment: commentsCollection }, ({ post, comment }) =>
    eq(post.id, comment.postId),
  )

3. Aggregation with groupBy + having

Use groupBy to group rows, then aggregate in select. Filter groups with having. The $selected namespace lets having and orderBy reference fields defined in select.

import { count, sum, gt } from '@tanstack/db'

const topCustomers = createLiveQueryCollection((q) =>
  q
    .from({ order: ordersCollection })
    .groupBy(({ order }) => order.customerId)
    .select(({ order }) => ({
      customerId: order.customerId,
      totalSpent: sum(order.amount),
      orderCount: count(order.id),
    }))
    .having(({ $selected }) => gt($selected.totalSpent, 1000))
    .orderBy(({ $selected }) => $selected.totalSpent, 'desc')
    .limit(10),
)

Without groupBy, aggregates in select treat the entire collection as one group:

const stats = createLiveQueryCollection((q) =>
  q.from({ user: usersCollection }).select(({ user }) => ({
    totalUsers: count(user.id),
    avgAge: avg(user.age),
  })),
)

4. Standalone derived collection with createLiveQueryCollection

Derived collections are themselves collections. Use one as a source for another query to cache intermediate results:

// Base derived collection
const activeUsers = createLiveQueryCollection((q) =>
  q.from({ user: usersCollection }).where(({ user }) => eq(user.active, true)),
)

// Second query uses the derived collection as its source
const activeUserPosts = createLiveQueryCollection((q) =>
  q
    .from({ user: activeUsers })
    .join({ post: postsCollection }, ({ user, post }) =>
      eq(user.id, post.userId),
    )
    .select(({ user, post }) => ({
      userName: user.name,
      postTitle: post.title,
    })),
)

Create derived collections once at module scope and reuse them. Do not recreate on every render or navigation.

Live query collections default to gcTime: 5_000. An explicit gcTime: 0 is preserved and disables garbage collection for that derived collection.

Virtual Properties

Live query results include computed, read-only virtual properties on every row:

• $synced: true when no pending local optimistic write affects the row; false while one does. This is local mutation status, not proof that a backend uploaded, confirmed, or read back the row.
• $origin: "local" if the last confirmed change came from this client, otherwise "remote".
• $key: the row key for the result.
• $collectionId: the source collection ID.

These props are added automatically and can be used in where, select, and orderBy clauses. Do not persist them back to storage.

Includes (Subqueries in Select)

Embed a correlated subquery inside select() to produce hierarchical (nested) data. The subquery must contain a where with an eq() that correlates a parent field with a child field.

Collection includes (default)

Return a child Collection on each parent row:

import { eq, createLiveQueryCollection } from '@tanstack/db'

const projectsWithIssues = createLiveQueryCollection((q) =>
  q.from({ p: projectsCollection }).select(({ p }) => ({
    id: p.id,
    name: p.name,
    issues: q
      .from({ i: issuesCollection })
      .where(({ i }) => eq(i.projectId, p.id))
      .select(({ i }) => ({
        id: i.id,
        title: i.title,
      })),
  })),
)

// Each row's `issues` is a live Collection
for (const project of projectsWithIssues) {
  console.log(project.name, project.issues.toArray)
}

Array includes with toArray()

Wrap the subquery in toArray() to get a plain array instead of a Collection:

import { eq, toArray, createLiveQueryCollection } from '@tanstack/db'

const messagesWithParts = createLiveQueryCollection((q) =>
  q.from({ m: messagesCollection }).select(({ m }) => ({
    id: m.id,
    contentParts: toArray(
      q
        .from({ c: chunksCollection })
        .where(({ c }) => eq(c.messageId, m.id))
        .orderBy(({ c }) => c.timestamp)
        .select(({ c }) => c.text),
    ),
  })),
)
// row.contentParts is string[]

Plain values with materialize()

Use materialize() when the parent row should hold a plain snapshot rather than a child collection:

import { eq, materialize, createLiveQueryCollection } from '@tanstack/db'

const issuesWithProject = createLiveQueryCollection((q) =>
  q.from({ issue: issuesCollection }).select(({ issue }) => ({
    ...issue,
    project: materialize(
      q
        .from({ project: projectsCollection })
        .where(({ project }) => eq(project.id, issue.projectId))
        .findOne(),
    ),
  })),
)
// row.project is Project | undefined

For a multi-row subquery, materialize() returns Array<T> like toArray(). For a subquery ending in findOne(), it returns T | undefined. In both cases, the parent row is re-emitted when the child result changes.

Concatenated scalar with concat(toArray())

Wrap toArray() in concat() to join the scalar results into a single string:

import { eq, toArray, concat, createLiveQueryCollection } from '@tanstack/db'

const messagesWithContent = createLiveQueryCollection((q) =>
  q.from({ m: messagesCollection }).select(({ m }) => ({
    id: m.id,
    content: concat(
      toArray(
        q
          .from({ c: chunksCollection })
          .where(({ c }) => eq(c.messageId, m.id))
          .orderBy(({ c }) => c.timestamp)
          .select(({ c }) => c.text),
      ),
    ),
  })),
)
// row.content is a single concatenated string

Includes rules

• The subquery must have a where clause with an eq() correlating a parent alias with a child alias. The library extracts this automatically as the join condition.
• toArray() works with both scalar selects (e.g., select(({ c }) => c.text) → string[]) and object selects (e.g., select(({ c }) => ({ id: c.id, title: c.title })) → Array<{id, title}>).
• materialize() returns an array, or one value for a findOne() subquery. Like toArray(), it must be a top-level value in select() and cannot be nested inside coalesce(), eq(), or another expression.
• concat(toArray()) requires a scalar select to concatenate into a string.
• Collection includes (bare subquery) require an object select.
• Includes subqueries are compiled into the same incremental pipeline as the parent query -- they are not separate live queries.

One-Shot Queries with queryOnce

For non-reactive, one-time snapshots use queryOnce. It creates a live query collection, preloads it, extracts the results, and cleans up automatically.

import { eq, queryOnce } from '@tanstack/db'

const activeUsers = await queryOnce((q) =>
  q
    .from({ user: usersCollection })
    .where(({ user }) => eq(user.active, true))
    .select(({ user }) => ({ id: user.id, name: user.name })),
)

// With findOne — resolves to T | undefined
const user = await queryOnce((q) =>
  q
    .from({ user: usersCollection })
    .where(({ user }) => eq(user.id, userId))
    .findOne(),
)

Use queryOnce for scripts, loaders, data export, tests, or AI/LLM context building. For UI bindings and reactive updates, use live queries instead.

Reactive Effects (createEffect)

Reactive effects respond to query result changes without materializing the full result set. Effects fire callbacks when rows enter, exit, or update within a query result — like a database trigger on an arbitrary live query.

import { createEffect, eq } from '@tanstack/db'

const effect = createEffect({
  query: (q) =>
    q
      .from({ msg: messagesCollection })
      .where(({ msg }) => eq(msg.role, 'user')),
  skipInitial: true,
  onEnter: async (event, ctx) => {
    await processNewMessage(event.value, { signal: ctx.signal })
  },
  onExit: (event) => {
    console.log('Message left result set:', event.key)
  },
  onError: (error, event) => {
    console.error(`Failed to process ${event.key}:`, error)
  },
})

// Dispose when no longer needed
await effect.dispose()

Key options: id (optional), query, skipInitial (skip existing rows on init), onEnter, onUpdate, onExit, onBatch, onError, onSourceError. The ctx.signal aborts when the effect is disposed.

Common Mistakes

CRITICAL: Using === instead of eq()

JavaScript === in a where callback returns a boolean primitive, not an expression object. Throws InvalidWhereExpressionError.

// WRONG
q.from({ user: usersCollection }).where(({ user }) => user.active === true)

// CORRECT
q.from({ user: usersCollection }).where(({ user }) => eq(user.active, true))

CRITICAL: Filtering in JS instead of query operators

JS .filter() / .map() on the result array throws away incremental maintenance -- the JS code re-runs from scratch on every change.

// WRONG -- re-runs filter on every change
const { data } = useLiveQuery({
  query: (q) => q.from({ todos: todosCollection }),
})
const active = data.filter((t) => t.completed === false)

// CORRECT -- incrementally maintained
const { data } = useLiveQuery({
  query: (q) =>
    q
      .from({ todos: todosCollection })
      .where(({ todos }) => eq(todos.completed, false)),
})

HIGH: Not using the full operator set

The library provides string functions (upper, lower, length, concat), math (add, subtract, multiply, divide), utility functions (coalesce, caseWhen), and aggregates (count, sum, avg, min, max). All are incrementally maintained. Prefer them over JS equivalents.

// WRONG
.fn.select((row) => ({
  name: row.user.name.toUpperCase(),
  total: row.order.price + row.order.tax,
}))

// CORRECT
.select(({ user, order }) => ({
  name: upper(user.name),
  total: add(order.price, order.tax),
  displayName: coalesce(user.displayName, user.name, 'Unknown'),
}))

Math expressions also work in orderBy(). When a computed expression is used with limit(), lazy-loading optimization is skipped and all matching rows load before sorting. Literal values such as Date.now() are captured when the query is created; recreate the query when the value must advance.

HIGH: Missing conditional expression helpers

Use coalesce() for null/undefined fallbacks and caseWhen() for conditional computed fields. JavaScript operators like || or ternaries do not build query expressions inside standard .select() callbacks.

// WRONG -- document.title is a query ref, not a runtime string
.select(({ document }) => ({
  displayTitle: document.title || 'Untitled document',
}))

// CORRECT -- fallback for null/undefined
.select(({ document }) => ({
  displayTitle: coalesce(document.title, 'Untitled document'),
}))

// CORRECT -- fallback for null/undefined and empty string
.select(({ document }) => ({
  displayTitle: caseWhen(
    eq(coalesce(document.title, ''), ''),
    'Untitled document',
    document.title,
  ),
}))

Use fn.select() only when you genuinely need arbitrary JavaScript; it cannot be optimized like expression-based .select().

HIGH: .distinct() without .select()

distinct() deduplicates by the selected columns. Without select(), throws DistinctRequiresSelectError.

// WRONG
q.from({ user: usersCollection }).distinct()

// CORRECT
q.from({ user: usersCollection })
  .select(({ user }) => ({ country: user.country }))
  .distinct()

HIGH: .having() without .groupBy()

having filters aggregated groups. Without groupBy, there are no groups. Throws HavingRequiresGroupByError.

// WRONG
q.from({ order: ordersCollection }).having(({ order }) =>
  gt(count(order.id), 5),
)

// CORRECT
q.from({ order: ordersCollection })
  .groupBy(({ order }) => order.customerId)
  .having(({ order }) => gt(count(order.id), 5))

HIGH: .limit() / .offset() without .orderBy()

Without deterministic ordering, limit/offset results are non-deterministic and cannot be incrementally maintained. Throws LimitOffsetRequireOrderByError.

// WRONG
q.from({ user: usersCollection }).limit(10)

// CORRECT
q.from({ user: usersCollection })
  .orderBy(({ user }) => user.name)
  .limit(10)

HIGH: Join condition using non-eq() operator

The differential dataflow join operator only supports equality joins. Using gt(), like(), etc. throws JoinConditionMustBeEqualityError.

// WRONG
q.from({ user: usersCollection }).join(
  { post: postsCollection },
  ({ user, post }) => gt(user.id, post.userId),
)

// CORRECT
q.from({ user: usersCollection }).join(
  { post: postsCollection },
  ({ user, post }) => eq(user.id, post.userId),
)

MEDIUM: Passing source directly instead of {alias: collection}

from() and join() require sources wrapped as {alias: collection}. Passing the collection directly throws InvalidSourceTypeError.

// WRONG
q.from(usersCollection)

// CORRECT
q.from({ users: usersCollection })

MEDIUM: Using unsafe select alias paths

Select alias path segments named __proto__, prototype, or constructor throw UnsafeAliasPathError. Use ordinary data-field names; do not suppress this prototype-pollution guard.

Tension: Query expressiveness vs. IVM constraints

The query builder looks like SQL but has constraints that SQL does not:

• Equality joins only -- eq() is the only allowed join condition operator.
• orderBy required for limit/offset -- non-deterministic pagination cannot be incrementally maintained.
• distinct requires select -- deduplication needs an explicit projection.
• fn.select() cannot be used with groupBy() -- the compiler must statically analyze select to discover aggregate functions.

These constraints exist because the underlying d2ts differential dataflow engine requires them for correct incremental view maintenance.

See also: react-db/SKILL.md for React hooks (useLiveQuery, useLiveSuspenseQuery, useLiveInfiniteQuery).

References

• Query Operators Reference -- full signatures and examples for all operators, functions, and aggregates.