target-snowflake
Target for Snowflake.
Built with the Meltano Singer SDK.
Capabilities
aboutstream-mapsschema-flatteningtarget-schema
Settings
| Setting | Required | Default | Description |
|---|---|---|---|
| user | True | None | The login name for your Snowflake user. |
| password | False | None | The password for your Snowflake user. |
| private_key | False | None | The private key contents. For KeyPair authentication either private_key or private_key_path must be provided. |
| private_key_path | False | None | Path to file containing private key. For KeyPair authentication either private_key or private_key_path must be provided. |
| private_key_passphrase | False | None | Passphrase to decrypt private key if encrypted. |
| oauth_access_token | False | None | OAuth2.0 access token for authentication. Token should be valid and not expired. |
| account | True | None | Your account identifier. See Account Identifiers. |
| database | True | None | The initial database for the Snowflake session. |
| schema | False | None | The initial schema for the Snowflake session. |
| warehouse | False | None | The initial warehouse for the session. |
| role | False | None | The initial role for the session. |
| add_record_metadata | False | 1 | Whether to add metadata columns. |
| clean_up_batch_files | False | 1 | Whether to remove batch files after processing. |
| default_target_schema | False | None | The default target database schema name to use for all streams. |
| hard_delete | False | 0 | Hard delete records. |
| load_method | False | upsert | Controls how records are written to the destination table. 'append-only' always uses COPY INTO, writing every input record as a new row regardless of key properties, without merging or truncating. 'upsert' (default) uses MERGE INTO, matching on key properties to update existing rows and insert new ones. 'overwrite' truncates the table then uses COPY INTO, replacing all existing rows — faster for initial loads but destructive if run on a populated table. |
| ingestion_method | False | file_staging | How records are loaded into Snowflake. 'file_staging' (default) stages local batch files and loads them with COPY INTO/MERGE INTO, per load_method; this requires a running warehouse. 'snowpipe_streaming' ingests rows directly via the Snowpipe Streaming API, with no warehouse required and billing based on data ingested. Only load_method: append-only and key-pair authentication are supported in this mode, and hard_delete is not supported. Requires the snowpipe extra: pip install 'meltanolabs-target-snowflake[snowpipe]' (Python 3.9-3.13 only). |
| batch_size_rows | False | None | Maximum number of rows in each batch. |
| validate_records | False | 1 | Whether to validate the schema of the incoming streams. |
| stream_maps | False | None | Config object for stream maps capability. For more information check out Stream Maps. |
| stream_map_config | False | None | User-defined config values to be used within map expressions. |
| faker_config | False | None | Config for the Faker instance variable fake used within map expressions. Only applicable if the plugin specifies faker as an additional dependency (through the singer-sdk faker extra or directly). |
| faker_config.seed | False | None | Value to seed the Faker generator for deterministic output: https://faker.readthedocs.io/en/master/#seeding-the-generator |
| faker_config.locale | False | None | One or more LCID locale strings to produce localized output for: https://faker.readthedocs.io/en/master/#localization |
| flattening_enabled | False | None | 'True' to enable schema flattening and automatically expand nested properties. |
| flattening_max_depth | False | None | The max depth to flatten schemas. |
| use_browser_authentication | False | False | If authentication should be done using SSO (via external browser). See See SSO browser authentication. |
A full list of supported settings and capabilities is available by running: target-snowflake --about
Initializing a Snowflake Account
This target has an interactive feature that will help you get a Snowflake account initialized with everything needed to get started loading data.
- User
- Role
- Warehouse
- Database
- Proper grants
The CLI will ask you to provide information about the new user/role/etc. you want to create but it will also need SYSADMIN credentials to execute the queries. You should prepare the following inputs:
- Account
- User that has SYSADMIN and SECURITYADMIN access. These comes default with the user that created the Snowflake account.
- The password for your SYSADMIN user.
Run the following command to get started with the interactive CLI. Note - the CLI will print the SQL queries it is planning to run and confirm with you before it makes any changes.
uv run target-snowflake --initialize
# Alternatively using Meltano CLI
meltano invoke target-snowflake --initialize
The CLI also has a "dry run" mode that will print the queries without executing them.
Check out the demo of this on YouTube.
Configure using environment variables
This Singer target will automatically import any environment variables within the working directory's
.env if the --config=ENV is provided, such that config values will be considered if a matching
environment variable is set either in the terminal context or in the .env file.
Usage
You can easily run target-snowflake by itself or in a pipeline using Meltano.
Executing the Target Directly
target-snowflake --version
target-snowflake --help
# Test using the "Carbon Intensity" sample:
tap-carbon-intensity | target-snowflake --config /path/to/target-snowflake-config.json
Developer Resources
Initialize your Development Environment
curl -LsSf https://astral.sh/uv/install.sh | sh # or see https://docs.astral.sh/uv/getting-started/installation/
uv sync --all-extras --dev
Create and Run Tests
Create tests within the target_snowflake/tests subfolder and
then run:
uv run pytest
You can also test the target-snowflake CLI interface directly using uv run:
uv run target-snowflake --help
Testing with Meltano
Note: This target will work in any Singer environment and does not require Meltano. Examples here are for convenience and to streamline end-to-end orchestration scenarios.
Your project comes with a custom meltano.yml project file already created.
Next, install Meltano (if you haven't already) and any needed plugins:
# Initialize meltano within this directory
cd target-snowflake
uvx meltano install
Now you can test and orchestrate using Meltano:
# Test invocation:
meltano invoke target-snowflake --version
# OR run a test `elt` pipeline with the Carbon Intensity sample tap:
meltano run tap-carbon-intensity target-snowflake
SDK Dev Guide
See the dev guide for more instructions on how to use the Meltano SDK to develop your own Singer taps and targets.
1 maintainer
Release files for meltanolabs-target-snowflake 0.20.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| meltanolabs_target_snowflake-0.20.0.tar.gz | 25.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| meltanolabs_target_snowflake-0.20.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size:55.4 kB
Release files / meltanolabs_target_snowflake-0.20.0.tar.gz
| Download URL | meltanolabs_target_snowflake-0.20.0.tar.gz |
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| Size | 25.2 kB |
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| Uploaded via |
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