1. dialects
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        • Add a card, through a Stripe-hosted setup session
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        • Start a conversation
        • Every support conversation, open first
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        • One conversation, with who is in it and who is connected
        • Rename a group; open or close a support conversation
        • The lines, oldest first
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    • Administration
      • Users
        • Every account
        • One account, with everything hanging off it
        • Grant or revoke admin
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      • Platform
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        • What kind of admin the caller is, and which scopes they hold
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        • Every admin, and the scopes each resolves to
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        • Every team, with its owner and size
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        • Hand the team to another member
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        • File a raw message, as if it had arrived
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    • Databases
      • Databases
        • Data stores
          • Every data store on the account
          • Provision a data store
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          • Report what it is using
          • How to reach a data store
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        • Schema and objects
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          • Create one, and apply it
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          • One table
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          • A plan compiled to statements, recording nothing
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          • Record one
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          • Take a backup
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        • Policies
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          • One policy
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          • Evaluate the periodic policies now
          • Who is behind a credential
        • Passwordless
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          • Issue a passwordless session (v1)
          • Revoke a passwordless session
          • Bind a session to a device key
          • Issue a v2 session for a host to bind
          • Redeem an enrolment ticket on the host
          • Check a passwordless credential
          • Run one described query under a passwordless credential
        • Database roles
          • The database's roles
          • Define a role
          • One role
          • Change what a role permits
          • Delete a role, and revoke every key granted it
          • Grant a role, which mints a key
          • Who holds a role
          • The api keys bound to a role
        • Pools
          • A database's connection pools, and how busy each is
          • Open another pool
          • Rename a pool or change its size
          • Close a pool
        • Data plane
          • Run a query against a database
          • Several statements, in order, over one connection
          • Is this database answering
          • What the proxy itself is holding
        • Transfers
          • The strategies this account's tier may use
          • Price a transfer without creating it
          • The account's transfer jobs, newest first
          • Create a transfer job
          • One job, and whether its certificate holds
          • Cancel an unfinished job
          • Start a created job, confirming its price
          • Report a job's status (the runner, or the owner's side of a local run)
        • Every database on the account
        • Provision a database
        • Change a database that is already running
        • One database
        • Deprovision it
        • Read or write it
        • Report what it is using
        • The engines this API will provision
        • Where a managed database can be put
    • Teams
      • Teams
        • Members
          • Who is on it
          • Invite somebody
          • Accept an invitation
          • Change somebody's role
          • Remove somebody
        • Projects
          • The projects a team runs
          • Start one
          • Rename a project, or move its environment
          • Delete a project
          • One project, and what is in it
          • Put a database or store in it
          • What is in a project
          • Take one out
        • The teams this account is on
        • Start one
        • The twelve roles, and what each may do
        • Rename a team
        • Close a team
        • One team
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    • Schemas
      • Error
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      • ServiceSession
      • DatabaseRole
      • TransferEndpoint
      • TransferJobRequest
      • TransferQuote
      • TransferStrategy
      • TransferJob
      • TransferJobAccess
      • Pool
      • PoolAllowance
      • BillingSubscription
      • Invoice
      • BillingContact
      • PaymentMethod
      • UpcomingCharges
      • TeamBilling
      • TeamKerberosRealm
      • TeamSsoDomain
      • TeamSsoResponse
      • StoreConnection
      • BatchFailure
      • ProxyStatus
  1. dialects

DuckDB Dialect

Overview#

DuckDB is an embedded, in-process OLAP (analytical)
database. Its deployment model mirrors SQLite — a single local file or an
in-memory instance, with no server, host, port, or authentication — but its SQL
engine is columnar and analytics-first: real window functions, recursive CTEs,
rich composite types (LIST/STRUCT/MAP/UNION), native sequences, a real
extension system (INSTALL/LOAD), and first-class Parquet/CSV/JSON table
functions.
PropertyValue
Dialect nameduckdb
Extendsnothing — implements Dialect directly
Driverduckdb
Cloud SDKnone
Default portnone — embedded
Local runtimeembedded — a file or :memory:
Key facts (from src/dialects/duckdb/index.ts):
Dialect name is 'duckdb'; the driver library is the duckdb npm package.
Embedded, single-process, single-user. There is no host/port/
username/password. Those fields are accepted on the config object for API
parity with networked dialects but are silently ignored.
The duckdb driver's public API is callback-based; the dialect wraps every
call (Database, connection.all, connection.run, connection.exec) in
Promises internally.
Columnar/analytical engine: it is optimized for large scans and aggregations,
not high-frequency single-row OLTP writes.

Quick start#

Install#

$ npm install ts-prorm-orm duckdb
$ pnpm add ts-prorm-orm duckdb
$ yarn add ts-prorm-orm duckdb
$ bun add ts-prorm-orm duckdb

Connect#

import { Prorm } from 'ts-prorm-orm';

export const db = new Prorm({
  dialect: 'duckdb',
  storage: './analytics.duckdb', // or ':memory:'
});
import { Prorm } from 'ts-prorm-orm';

export const db = new Prorm({
  dialect: 'duckdb',
  url: 'duckdb:./analytics.duckdb',
});
A URL is folded into host, port, database, username and password before the dialect is built; any of those passed alongside it wins.

Define a model#

import { DataTypes } from 'ts-prorm-orm';

const User = db.define('User', {
  id: { type: DataTypes.INTEGER(), primaryKey: true, autoIncrement: true },
  email: { type: DataTypes.STRING(255), allowNull: false, unique: true },
  name: { type: DataTypes.STRING(100) },
});

await db.sync(); // CREATE TABLE — see Generated SQL below

Query#

import { Op } from 'ts-prorm-orm';

await User.create({ email: 'ada@example.com', name: 'Ada' });

const page = await User.findAll({
  where: { name: { [Op.like]: 'A%' } },
  order: [['id', 'ASC']],
  limit: 20,
  offset: 40,
});

Generated SQL#

Each block is the statement the model call above it hands the dialect's query(), captured with the driver stubbed out. The model layer inlines the values.

Create table#

db.sync() for the model in the Quick start:
CREATE TABLE

Insert, update and delete#

await User.create({ email: 'ada@example.com', name: 'Ada' });
await User.update({ name: 'Grace' }, { where: { email: 'ada@example.com' } });
await User.destroy({ where: { id: 1 } });

Upsert#

await User.upsert({ id: 1, email: 'ada@example.com', name: 'Ada Lovelace' });
upsert() also reads the row by primary key before and after the write, to return the instance.

Pagination#

await User.findAll({
  where: { name: { [Op.like]: 'A%' } },
  order: [['id', 'ASC']],
  limit: 20,
  offset: 40,
});

Transaction#

await db.transaction(async (t) => {
  await User.create({ email: 'grace@example.com', name: 'Grace' }, { transaction: t });
  await User.update({ name: 'Grace Hopper' }, { where: { email: 'grace@example.com' }, transaction: t });
});
[!WARNING] No savepoints
Nested transactions need savepoints, and duckdb has none. Run the work in a single transaction, or restructure it so nothing nests.

DISTINCT ON#

distinctOn keeps the first row of each group in order — here the newest row per name:
const latest = db.getDialectInstance()!.buildSelectQuery({
  tableName: 'users',
  distinctOn: ['name'],
  order: [['name', 'ASC'], ['id', 'DESC']],
});
await db.query(latest.sql, { replacements: latest.values });
Type mapping for the portable descriptors: STRING → VARCHAR(255), auto-increment INTEGER → INTEGER, BOOLEAN → BOOLEAN, DATE → TIMESTAMP, UUID → UUID, JSON → JSON. The type comparison lines the major engines up side by side.

Connection#

import { Prorm } from 'ts-prorm-orm';

// In-memory (default): fast, ephemeral, gone when the process exits.
const mem = new Prorm({
  dialect: 'duckdb',
  storage: ':memory:',
});

// File-backed: a single on-disk DuckDB database file.
const db = new Prorm({
  dialect: 'duckdb',
  storage: './analytics.duckdb',
});
Options accepted by the dialect (DuckDBDialectOptions):
storage — file path to the database, or ':memory:'. Defaults to
':memory:'.
readonly — open the database in read-only mode (access_mode: READ_ONLY).
config — a Record<string, string> of DuckDB config options passed straight
through to the Database constructor, e.g. { max_memory: '4GB' }.
const ro = new Prorm({
  dialect: 'duckdb',
  storage: './analytics.duckdb',
  dialectOptions: { readonly: true, config: { max_memory: '4GB' } },
});
Notes:
The connect callback only resolves once the native handle has actually
opened, so open failures (corrupt file, permission denied, read-only open
against a locked writer) surface at connect() rather than on the first
query.
getDatabaseVersion() runs SELECT version().

Identifiers and value escaping#

DuckDB uses standard SQL literals, so escaping differs from MySQL-family
dialects:
Identifiers are double-quoted: escapeId('my col') → "my col"
(embedded " doubled).
Booleans escape to TRUE / FALSE (not 0/1).
Date values escape to TIMESTAMP '2024-01-01 00:00:00.000'.
Buffer values escape to a '\xNN...'::BLOB cast.
JS arrays escape to DuckDB list literals: [1, 2, 3].
Positional parameters use ? placeholders (SQLite-style).

Data types#

getDataTypeSql maps ORM type descriptors to DuckDB types:
ORM type descriptorGenerated SQL
{ key: 'STRING' }VARCHAR(255)
{ key: 'STRING', length: 100 }VARCHAR(100)
{ key: 'TEXT' }VARCHAR
{ key: 'INTEGER' }INTEGER
{ key: 'INTEGER', unsigned: true }UINTEGER
{ key: 'BIGINT' }BIGINT
{ key: 'BIGINT', unsigned: true }UBIGINT
{ key: 'FLOAT' }REAL
{ key: 'DOUBLE' }DOUBLE
{ key: 'DECIMAL', precision: 12, scale: 4 }DECIMAL(12,4)
{ key: 'BOOLEAN' }BOOLEAN
{ key: 'DATE' }TIMESTAMP
{ key: 'DATEONLY' }DATE
{ key: 'TIME' }TIME
{ key: 'BLOB' }BLOB
{ key: 'JSON' } / { key: 'JSONB' }JSON
{ key: 'UUID' }UUID
{ key: 'ENUM', values: ['a', 'b'] }VARCHAR CHECK(col IN ('a','b'))
Note that DATE maps to TIMESTAMP (date + time), while DATEONLY maps to a
bare DATE.

Composite (nested) types#

DuckDB has genuine nested types, and the dialect emits them directly:
{ key: 'LIST', type: <elementType> } (or ARRAY) → <elementType>[], e.g.
INTEGER[]. Falls back to VARCHAR[] when the element type is omitted.
{ key: 'STRUCT', fields: { a: <type>, ... } } → STRUCT(a TYPE, ...).
{ key: 'MAP', keyType, valueType } → MAP(keyType, valueType).
{ key: 'UNION', fields: { tag: <type>, ... } } → UNION(tag TYPE, ...).

ENUM is emulated#

DuckDB has a native ENUM, but it requires a separately named type
(CREATE TYPE ... AS ENUM (...)) with out-of-band lifecycle management. To keep
column definitions self-contained, the dialect instead emulates enums as
VARCHAR with a CHECK constraint (the same approach SQLite uses).

Auto-increment and sequences#

DuckDB has no AUTOINCREMENT keyword — it uses native sequences. When a
column is defined with autoIncrement: true, the dialect first creates a
backing sequence (seq_<table>_<column>) and defines the column with
DEFAULT nextval('seq_...').
Sequences are also exposed as a first-class, native feature:
await db.dialect.createSequence({ name: 'order_ids', startWith: 1000, incrementBy: 1 });
const next = await db.dialect.nextSequenceValue('order_ids');
const seqs = await db.dialect.listSequences();
createIdentityColumn is emulated the same way (DuckDB has no
GENERATED ... AS IDENTITY): it creates a sequence and sets the column default
to nextval(...).

Upsert (ON CONFLICT)#

DuckDB uses PostgreSQL/SQLite-style INSERT ... ON CONFLICT. Because the
conflict target must be named explicitly, an upsert requires conflictFields
(the PRIMARY KEY or UNIQUE columns) unless doNothing is set:
db.dialect.buildUpsertQuery(
  'kv',
  { k: 'a', v: 1 },
  { conflictFields: ['k'] },
);
updateOnDuplicate: ['v'] restricts the DO UPDATE SET list to those columns.
doNothing: true emits ON CONFLICT DO NOTHING (with an optional target).
conflictTargets accepts multiple chained ON CONFLICT (...) DO ... targets.
RETURNING is supported (returning: true → RETURNING *).
Omitting conflictFields on a DO UPDATE upsert throws:
DuckDB upsert requires `conflictFields` naming the PRIMARY KEY or UNIQUE columns
to resolve conflicts against (e.g. { conflictFields: ["id"] }), unless
`doNothing` is set.

Transactions#

Top-level transactions use BEGIN TRANSACTION / COMMIT / ROLLBACK. Nested
transactions are emulated with SAVEPOINT / RELEASE SAVEPOINT /
ROLLBACK TO SAVEPOINT (see DuckDBTransaction).
const tx = await db.dialect.startTransaction();
try {
  await db.dialect.query('INSERT INTO t (id) VALUES (1)');
  await tx.commit();
} catch (err) {
  await tx.rollback();
  throw err;
}

DuckDB-specific value-add: files as tables#

DuckDB's signature capability is querying Parquet/CSV/JSON files directly as
tables, and exporting results back out. The dialect exposes builders that return
table-function expressions usable in a FROM clause:
// SELECT ... FROM read_parquet('data/*.parquet', hive_partitioning=true)
const src = db.dialect.readParquet('data/*.parquet', { hivePartitioning: true });
const rows = await db.dialect.query(`SELECT region, SUM(amount) AS total FROM ${src} GROUP BY region`);

// CSV and JSON too:
db.dialect.readCsv('sales.csv', { header: true });          // read_csv_auto('sales.csv', header=true)
db.dialect.readJson('events.ndjson', { format: 'newline_delimited' });
Export a query straight to a file with copyTo:
await db.dialect.copyTo(
  'SELECT * FROM sales',
  'out/sales',
  'PARQUET',
  { partitionBy: ['region'], overwrite: true, compression: 'zstd' },
);

Reading remote data (S3 / httpfs)#

createExtension('httpfs') installs and loads the extension but does not supply
credentials. Two mechanisms are exposed:
await db.dialect.createExtension('httpfs');

// Global SET variables (simplest, one credential set at a time):
await db.dialect.configureS3Credentials({
  region: 'us-east-1',
  accessKeyId: '...',
  secretAccessKey: '...',
});

// Or the newer, recommended named-secret mechanism (scoped, can coexist):
await db.dialect.createSecret('my_bucket', {
  keyId: '...',
  secret: '...',
  region: 'us-east-1',
  scope: 's3://my-bucket',
});

Extensions#

Unlike most dialects, DuckDB's extension system is implemented for real:
await db.dialect.createExtension('parquet');   // INSTALL parquet; LOAD parquet;
const has = await db.dialect.hasExtension('parquet');
const all = await db.dialect.getExtensions();
There is no uninstall — dropExtension() throws. To stop using an
extension, simply do not LOAD it in future connections.

Attaching other databases#

DuckDB can attach additional database files (DuckDB, or SQLite/Postgres via the
respective extension) and query them as alias.table:
await db.dialect.attachDatabase('./other.duckdb', 'other');
await db.dialect.query('SELECT * FROM other.users');
await db.dialect.detachDatabase('other');
CREATE DATABASE is emulated via ATTACH (DuckDB has no CREATE DATABASE
statement — a "database" is a file). SELECT * EXCLUDE (...) is also supported
through the attribute builder for column exclusion.

Honest limitations#

Several features from other dialects are not supported and throw a clear
error rather than silently doing nothing:
Triggers — not supported (createTrigger/dropTrigger throw). Move
reactive logic into application code.
Stored procedures — no procedural language. createStoredProcedure,
executeStoredProcedure, etc. throw; the closest analogue is a scalar/table
MACRO or a view, which the error message points to.
Materialized views — no CREATE MATERIALIZED VIEW. Use
CREATE TABLE ... AS SELECT ... (re-run to refresh) or copyTo() a Parquet
file plus readParquet().
Foreign Data Wrappers — PostgreSQL-only; all FDW methods throw.
Row-level security / policies — not supported.
User / role / privilege management — DuckDB is single-user; all
user/role/grant methods throw.
ALTER TABLE ADD FOREIGN KEY — not supported; define foreign keys at
CREATE TABLE time instead.
Partial indexes — CREATE INDEX ... WHERE ... is unsupported;
addIndex with a where option throws.
Fulltext / spatial indexes — require the fts / spatial extensions;
createFulltextIndex / createSpatialIndex throw with guidance to use
PRAGMA create_fts_index(...) or the RTREE index type.
Table-level partitioning is emulated (child tables + a metadata table
a UNION ALL view, like SQLite), since DuckDB's real partitioning lives at
the storage layer via Hive-partitioned Parquet (copyTo/readParquet).
changeOwner — there is no per-table ownership model to change.

Caveats#

In-memory storage is ephemeral. With storage: ':memory:' (the default),
all data is lost when the process exits. Use a file path to persist.
Analytical, not OLTP. DuckDB shines at large scans and aggregations over
columnar data; it is not designed for high-concurrency single-row writes.
Single writer. As an embedded database, a file can have one read-write
process at a time; other processes must open it read-only.

Capabilities#

Computed from the code — capabilitiesOf() (src/transaction-support.ts),
whereSupportOf() (src/query-builders/expression-render.ts),
sqlObjectCapabilitiesOf() (src/sql-objects/capabilities.ts) and the
builders — by the scratch test described in the
capability matrix.
Capabilityduckdb
Transactions atomicyes
Savepointsno — a nested transaction() throws
Isolationup to REPEATABLE READ
Transaction modesread-only no; deferrable no; constraint deferral no
RETURNINGRETURNING on INSERT
UpsertINSERT … ON CONFLICT (…) DO UPDATE
JSON columnJSON (JSONB → JSON)
Vector columnFLOAT[3]
Array columnINTEGER[]
WHERE builder39 operator keys; $and/$or/$not; $exists: yes; $in subquery: yes; expression operands: yes
SQL objectsfamily duckdb: triggers no; procedures no; functions macro; materialized views emulated (app); sequences yes; enums named; RLS no
StreamingqueryStream() present; LISTEN absent; createExtension() present

Related reading#

All dialects — what each engine supports
Data types — how each type maps to this engine
Querying — how a FindOptions becomes SQL
Modified at 2026-10-04 00:40:16
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