Destinations

from dlt.destinations import postgres

pipeline = dlt.pipeline(
    destination=postgres()
)

from dlt.destinations import bigquery

pipeline = dlt.pipeline(
    destination=bigquery()
)

from dlt.destinations import snowflake

pipeline = dlt.pipeline(
    destination=snowflake()
)

from dlt.destinations import redshift

pipeline = dlt.pipeline(
    destination=redshift()
)

from dlt.destinations import duckdb

pipeline = dlt.pipeline(
    destination=duckdb(database="local.duckdb")
)

from dlt.destinations import motherduck

pipeline = dlt.pipeline(
    destination=motherduck()
)

from dlt.destinations import mssql

pipeline = dlt.pipeline(
    destination=mssql()
)

from dlt.destinations import synapse

pipeline = dlt.pipeline(
    destination=synapse()
)

from dlt.destinations import databricks

pipeline = dlt.pipeline(
    destination=databricks()
)

from dlt.destinations import clickhouse

pipeline = dlt.pipeline(
    destination=clickhouse()
)

from dlt.destinations import dremio

pipeline = dlt.pipeline(
    destination=dremio()
)

from dlt.destinations import sqlalchemy

pipeline = dlt.pipeline(
    destination=sqlalchemy()
)

from dlt.destinations import filesystem

pipeline = dlt.pipeline(
    destination=filesystem(bucket_url="s3://my-bucket")
)

from dlt.destinations import fabric

pipeline = dlt.pipeline(
    destination=fabric()
)

from dlt.destinations import athena

pipeline = dlt.pipeline(
    destination=athena()
)

from dlt.destinations import ducklake

pipeline = dlt.pipeline(
    destination=ducklake()
)

from dlt.destinations import qdrant

pipeline = dlt.pipeline(
    destination=qdrant()
)

from dlt.destinations import weaviate

pipeline = dlt.pipeline(
    destination=weaviate()
)

from dlt.destinations import lancedb

pipeline = dlt.pipeline(
    destination=lancedb()
)

from dlt.destinations import dummy

pipeline = dlt.pipeline(
    destination=dummy()  # For testing, discards all data
)

from dlt.destinations import destination

# Create custom destination from callable
@destination(batch_size=1000)
def my_destination(items, table):
    # Process items
    for item in items:
        print(item)

pipeline = dlt.pipeline(
    destination=my_destination
)

import dlt

pipeline = dlt.pipeline(
    pipeline_name="my_pipeline",
    destination="duckdb",
    dataset_name="my_dataset"
)

from dlt.destinations import postgres

pipeline = dlt.pipeline(
    pipeline_name="my_pipeline",
    destination=postgres(
        credentials="postgresql://user:pass@localhost/db"
    ),
    dataset_name="my_dataset"
)

[destination.postgres.credentials]
database = "mydb"
username = "user"
password = "password"
host = "localhost"
port = 5432

pipeline = dlt.pipeline(
    destination="postgres",  # Credentials loaded from secrets.toml
    dataset_name="my_dataset"
)

export DESTINATION__POSTGRES__CREDENTIALS__DATABASE="mydb"
export DESTINATION__POSTGRES__CREDENTIALS__PASSWORD="password"

destination(
    credentials="...",  # Connection credentials
    destination_name="custom_name",  # Override destination name
    environment="production"  # Environment suffix for dataset
)

@dlt.resource(write_disposition="merge", primary_key="id")
def my_resource():
    ...