Google Cloud Spanner Dialect
Overview#
Google Cloud Spanner is a fully-managed,
horizontally-scalable, strongly-consistent distributed SQL database. Unlike the
other distributed dialects in this codebase (cockroachdb is Postgres-wire,
tidb is MySQL-wire), Spanner is not wire-compatible with an existing
engine, so this dialect is a standalone Dialect implementation built on the
official @google-cloud/spanner driver rather than an extension of another
dialect.| Property | Value |
|---|
| Dialect name | spanner |
| Extends | nothing — implements Dialect directly |
| Driver | @google-cloud/spanner |
| Cloud SDK | @google-cloud/spanner |
| Default port | none — gRPC API |
| Local runtime | the Spanner emulator (emulator: true) |
Key facts (from src/dialects/spanner/index.ts):Dialect name is 'spanner'; the driver library is @google-cloud/spanner.
This dialect targets GoogleSQL, Spanner's native SQL dialect (backtick-quoted
identifiers, STRING(n)/INT64 types, @pN named parameters). It does not
target Spanner's PostgreSQL interface — connect() fails fast if the database
was provisioned with databaseDialect: POSTGRESQL (use the postgres dialect
for those). See GoogleSQL vs the PostgreSQL interface. There is no local SQL port. The dialect authenticates via Google Application
Default Credentials (ADC) or an explicit service-account key and addresses a
database by project / instance / database IDs, not host/port.
Quick start#
Install#
$ npm install ts-prorm-orm @google-cloud/spanner
$ pnpm add ts-prorm-orm @google-cloud/spanner
$ yarn add ts-prorm-orm @google-cloud/spanner
$ bun add ts-prorm-orm @google-cloud/spanner
Connect#
import { Prorm } from 'ts-prorm-orm';
export const db = new Prorm({
dialect: 'spanner',
dialectOptions: {
projectId: 'my-project',
instanceId: 'prod-instance',
databaseId: 'app-db',
},
});
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.[!WARNING] A plain INSERT
The engine has no conflict clause, so this upsert inserts and never updates an existing row.
await User.findAll({
where: { name: { [Op.like]: 'A%' } },
order: [['id', 'ASC']],
limit: 20,
offset: 40,
});
JSON#
[!NOTE] No JSON operator in the WHERE builder
DataTypes.JSON() maps to JSON, but this dialect's WHERE builder refuses Op.contains on it: Cannot render WHERE condition at meta.contains' is not implemented by its WHERE builder. The statement was not sent, because running it without the condition would match rows it should not.
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
capabilitiesOf() reports no savepoints for this dialect, so a transaction() nested inside another one throws.
Type mapping for the portable descriptors: STRING → STRING(255), auto-increment INTEGER → INT64, BOOLEAN → BOOL, DATE → TIMESTAMP, UUID → STRING(36), JSON → JSON. The type comparison lines the major engines up side by side.Connection#
Spanner-specific options are passed through dialectOptions:import { Prorm } from 'ts-prorm-orm';
const db = new Prorm({
dialect: 'spanner',
dialectOptions: {
projectId: 'my-gcp-project', // omit to use ADC's default project
instanceId: 'prod-instance', // required
databaseId: 'app-db', // required
// keyFilename: '/path/to/sa-key.json', // else falls back to ADC
},
});
await db.connect();
For the Spanner emulator, pass emulator: true (defaults apiEndpoint to
localhost:9010) alongside skipDialectCheck: true.SpannerDialectOptions (from the source):instanceId / databaseId — required; identify the Spanner database.
projectId — GCP project; falls back to the ADC default project when omitted.
keyFilename / credentials — explicit service-account auth. When both are
omitted, the driver uses GOOGLE_APPLICATION_CREDENTIALS / ambient ADC (GCE,
GKE, Cloud Run metadata server).
apiEndpoint / emulator — override the endpoint / target the local emulator.
queryOptions — forwarded to every database.run() (e.g. optimizer version).
skipDialectCheck: true — skip the automatic GoogleSQL-dialect assertion done
on connect().
Distributed SQL & consistency model#
Spanner shards data across servers by primary-key ranges and rebalances splits
automatically — there is no user-facing PARTITION BY (all the
createPartitionedTable/createPartition/attachPartition methods throw).
Interleaved tables (below) are the closest Spanner-native tool for physical
co-location, but they solve co-location, not logical partitioning.Every read-write transaction is externally consistent (TrueTime-ordered,
effectively stronger than SERIALIZABLE) by construction. There is no isolation-level
spectrum: startTransaction() accepts options.isolationLevel for interface
parity but ignores it with a warning rather than pretending to map it.GoogleSQL vs the PostgreSQL interface#
Spanner exposes two SQL dialects. This implementation emits GoogleSQL only.
On connect() it calls assertGoogleSqlDialect(), which queries the Database
Admin API and throws an actionable error if the database is in POSTGRESQL
mode. Pass skipDialectCheck: true to bypass this, or call it manually:await dialect.assertGoogleSqlDialect(); // throws if the DB is PostgreSQL-interface
Spanner-specific features#
Auto-generated keys — hotspot avoidance#
Spanner's docs explicitly discourage monotonically-increasing primary keys: they
concentrate every write on the single split holding the tail of the key range (a
hotspot). To keep the shared autoIncrement flag meaningful without reproducing
that anti-pattern, an autoIncrement column is mapped to a random, well-distributed
UUID (and a warning is logged):await db.dialect.createTable('users', {
id: { type: 'UUID', primaryKey: true, autoIncrement: true },
name: { type: 'STRING', length: 100 },
});
Note GoogleSQL declares the primary key after the column-list parentheses,
not inline. A table with no primary key throws — mark a column primaryKey: true
or pass options.primaryKey: ['col', ...].Bit-reversed sequences — ordered-but-distributed keys#
When you need a numeric key that is roughly ordered over time but still spread
across the keyspace, use a bit-reversed sequence instead of a plain counter:await db.dialect.createBitReversedSequence('order_seq', { startWithCounter: 1 });
const id = await db.dialect.nextBitReversedSequenceValue('order_seq');
// or, as a column default / SQL fragment:
db.dialect.nextBitReversedSequenceValueSql('order_seq');
// => GET_NEXT_SEQUENCE_VALUE(SEQUENCE `order_seq`)
Interleaved tables#
INTERLEAVE IN PARENT physically co-locates a child table's rows with their
parent row (e.g. Orders under Customers) so point look-ups and joins across
the relationship stay within one storage split. The child's primary key must
include the parent's primary key as a prefix:await db.dialect.createTable('Customers', {
CustomerId: { type: 'STRING', length: 36, primaryKey: true },
Name: { type: 'STRING', length: 200 },
});
await db.dialect.createInterleavedTable(
'Orders',
'Customers', // parent
{
CustomerId: { type: 'STRING', length: 36 },
OrderId: { type: 'STRING', length: 36 },
Total: { type: 'NUMBER' },
},
{ primaryKey: ['CustomerId', 'OrderId'], onDeleteCascade: true },
);
Covering (STORING) indexes and TTL#
addIndex's include option maps to Spanner's STORING (...) clause — a
covering index that duplicates listed columns so a lookup avoids a join back to
the base table. Row-TTL is expressed via a table-level row deletion policy:await db.dialect.addIndex('Orders', 'idx_orders_total', ['Total'], {
include: ['OrderId'], // STORING (`OrderId`)
});
await db.dialect.createTable('Events', {
Id: { type: 'UUID', primaryKey: true, autoIncrement: true },
CreatedAt: { type: 'DATE' }, // TIMESTAMP
}, {
rowDeletionPolicy: { column: 'CreatedAt', olderThanDays: 30 },
});
// ... ROW DELETION POLICY (OLDER_THAN(`CreatedAt`, INTERVAL 30 DAY))
Spanner has no arbitrary partial-index WHERE predicate; passing where to
addIndex logs a warning and is ignored (the closest analogue is NULL_FILTERED).Writes — SQL DML vs the Mutation API#
Spanner offers two write paths, and this dialect exposes both:1.
SQL DML (INSERT/UPDATE/DELETE) — always run inside a read-write
transaction. query() transparently wraps single DML statements in an
auto-committing transaction, since Spanner has no autocommit single-statement
DML path.
2.
The Mutation API — the recommended, primary path for bulk/blind
writes: it skips SQL parsing/planning and batches into one commit.
// Mutation API (recommended for bulk / blind writes)
await db.dialect.mutationInsert('users', [{ id: 'a', name: 'Ada' }]);
await db.dialect.mutationUpdate('users', [{ id: 'a', name: 'Ada L.' }]);
await db.dialect.mutationUpsert('users', [{ id: 'a', name: 'Ada' }]); // insert-or-update by PK
await db.dialect.mutationDelete('users', ['a']); // delete by PK
await db.dialect.bulkInsert('users', records); // uses mutationInsert
Upsert — INSERT OR UPDATE INTO#
Spanner has no ON CONFLICT clause. The SQL upsert fallback emits GoogleSQL's
INSERT OR UPDATE INTO:db.dialect.buildUpsertQuery('kv', { k: 'a', v: 1 });
Only the OR UPDATE variant is wired up (GoogleSQL also has OR IGNORE /
OR REPLACE, but there is no conflictAction option to select them). Prefer
mutationUpsert() over this SQL form for bulk writes.GoogleSQL DML has no RETURNING clause — passing returning to
buildInsertQuery/buildUpdateQuery/buildDeleteQuery logs a warning and is
ignored. UPDATE and DELETE always require a WHERE (an always-true WHERE TRUE
is emitted when none is given; truncate maps to DELETE FROM t WHERE TRUE since
there is no TRUNCATE).Transactions#
startTransaction/commitTransaction/rollbackTransaction bridge the driver's
callback-based database.runTransaction() into the imperative shape used
elsewhere. Contention surfaces as ABORTED (gRPC code 10); use isRetryableError()
to drive a retry loop (the driver also retries internally):const tx = await db.dialect.startTransaction();
try {
const spannerTx = (tx as any).spannerTransaction;
await spannerTx.runUpdate({ sql: 'UPDATE `users` SET `name` = @p1 WHERE `id` = @p2', params: { p1: 'Ada', p2: 'a' } });
await db.dialect.commitTransaction(tx);
} catch (err) {
await db.dialect.rollbackTransaction(tx);
if (db.dialect.isRetryableError(err)) { /* retry */ }
}
Read-only transactions (strong or stale/bounded-staleness reads) are a distinct
concept and are exposed separately, not through startTransaction():const rows = await db.dialect.runReadOnlyTransaction(
(run) => run('SELECT * FROM `users` WHERE `id` = @id', { id: 'a' }),
{ exactStaleness: { seconds: 15 } }, // lower-latency stale read
);
Spanner has no SAVEPOINT — the savepoint builders all throw.Type mapping#
getDataTypeSql maps ORM type descriptors to GoogleSQL types:| ORM type descriptor | Generated SQL |
|---|
{ key: 'STRING' } / { key: 'CHAR' } | STRING(255) (or length) |
{ key: 'TEXT' } | STRING(MAX) |
{ key: 'INTEGER' } / 'BIGINT' | INT64 |
{ key: 'FLOAT' } / 'DOUBLE' | FLOAT64 |
{ key: 'DECIMAL' } | NUMERIC |
{ key: 'BOOLEAN' } | BOOL |
{ key: 'DATE' } | TIMESTAMP |
{ key: 'DATEONLY' } | DATE |
{ key: 'BLOB' } | BYTES(MAX) (or length) |
{ key: 'UUID' } | STRING(36) |
{ key: 'JSON' } / 'JSONB' | JSON |
{ key: 'ENUM', values: [...] } | STRING(MAX) CHECK (col IN (...)) |
{ key: 'ARRAY', type: <t> } | ARRAY<t> |
TIME, SET, RANGE, INET, CIDR, MACADDR, and HSTORE have no native
equivalent and fall back to STRING(MAX) (HSTORE → JSON) with a warning.
GEOMETRY throws — Spanner has no built-in geometry/geography type.Not supported / caveats#
Methods that throw, because the underlying concept has no GoogleSQL analogue:Schemas / namespaces — createSchema/dropSchema throw; GoogleSQL has no
CREATE SCHEMA. quoteTable(name, schema) ignores schema with a warning.
Databases via SQL — created/dropped through the Admin API
(instance.createDatabase() / database.delete()), not DDL.
Extensions, Foreign Data Wrappers, row-level security, stored procedures /
procedural SQL — all throw; these are Postgres/relational concepts Spanner
lacks. Move procedural logic to the application layer.
CREATE USER / GRANT ... TO <user> — Spanner access is governed by Cloud
IAM plus GoogleSQL database roles. CREATE ROLE / DROP ROLE /
GRANT ROLE ... TO ROLE builders exist; per-user grants throw.
RENAME TABLE / RENAME COLUMN — not supported; add a new column/table,
backfill, drop the old one. Primary keys are fixed at CREATE TABLE time
(addConstraint with PRIMARY KEY throws).
DROP TABLE/DROP VIEW/DROP INDEX have no CASCADE — drop dependent
interleaved child tables and indexes explicitly first.
escape() and Date values. escape() has no column-type context, so a
JS Date is always emitted as a TIMESTAMP literal. GoogleSQL will reject
that for a DATE (DATEONLY) column. Pass a 'YYYY-MM-DD' string to
DATEONLY columns instead of a Date.
OFFSET requires LIMIT. GoogleSQL has no bare OFFSET n; when only an
offset is given, a very large LIMIT is emitted to satisfy the grammar.
Backups are an Admin API concept (createBackup/listBackups/getBackup/
deleteBackup/restoreDatabase), not BACKUP DATABASE DDL; these helpers
await the long-running operations to completion.
Window functions and (recursive) CTEs are standard GoogleSQL syntax and pass
straight through (buildWindowFunction, buildRecursiveCteQuery).
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.| Capability | spanner |
|---|
| Transactions atomic | yes |
| Savepoints | no — a nested transaction() throws |
| Isolation | up to SERIALIZABLE |
| Transaction modes | read-only no; deferrable no; constraint deferral no |
| RETURNING | not emitted; returning is accepted and ignored |
| Upsert | a plain INSERT: the engine has no conflict clause (see the page) |
| JSON column | JSON (JSONB → JSON) |
| Vector column | ARRAY<FLOAT32>(vector_length=>3) |
| Array column | ARRAY<INT64> |
| WHERE builder | 32 operator keys; $and/$or/$not; $exists: yes; $in subquery: yes; expression operands: yes |
| SQL objects | family unknown: triggers no; procedures no; functions no; materialized views no; sequences no; enums check; RLS no |
| Streaming | queryStream() present; LISTEN absent; createExtension() present |
Testing#
tests/dialects/spanner.test.ts exercises the dialect with a mocked driver, so nothing touches a server.Querying — how a FindOptions becomes SQL Modified at 2026-10-04 00:40:16