> For the complete documentation index, see [llms.txt](https://docs.algenta.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.algenta.ai/connectors/snowflake.md).

# Snowflake

By the end of this page you will have a saved `snowflake` connector that reaches your account, a confirmed `live` connection test, a browse listing of the tables it exposes, one of those tables onboarded as a queryable **dataset**, and a first [governed query](/guides/governed-query.md) returning rows from it. Once onboarded, the table becomes [governed data](/concepts/governed-data.md): the engine queries it under a typed, validated contract, so results stay deterministic and auditable.

Prerequisites: an API key and a base URL (see [Authentication](/getting-started/authentication.md)), and Snowflake credentials — an account identifier, a user, a password, and the database you want to query. Use `https://api.algenta.ai` for Algenta cloud, or your own origin such as `http://localhost:8000` for a self-hosted deployment.

{% hint style="info" %}
A `snowflake` connector takes these `config` fields: `account`, `user`, `password`, and `database` are required for the structured form; `warehouse` and `schema` are optional. Alternatively, supply a single `connection_string` DSN of the form `snowflake://user:password@account/database/schema?warehouse=WH`. These are the only Snowflake fields the engine reads.
{% endhint %}

{% stepper %}
{% step %}

### Set your credentials

Export your API key and base URL so every command below picks them up from the environment. Keep your Snowflake password in its own variable so it never appears in shell history inline.

```bash
export ALGENTA_API_KEY="$ALGENTA_API_KEY"
export ALGENTA_BASE_URL="https://api.algenta.ai"
export SNOWFLAKE_PASSWORD="$SNOWFLAKE_PASSWORD"
```

Verify the variables are set:

```bash
echo "${ALGENTA_API_KEY:?set ALGENTA_API_KEY}" >/dev/null && echo "key present"
echo "$ALGENTA_BASE_URL"
echo "${SNOWFLAKE_PASSWORD:?set SNOWFLAKE_PASSWORD}" >/dev/null && echo "password present"
```

**Expected result:** three lines print without error — `key present`, your base URL, and `password present`. If any line errors, export the missing variable before continuing.
{% endstep %}

{% step %}

### Confirm the engine accepts `snowflake`

Ask the engine which connector types it supports and confirm `snowflake` is in the list.

```bash
curl -s "$ALGENTA_BASE_URL/v1/connectors/types" \
  -H "Authorization: Bearer $ALGENTA_API_KEY"
```

**Expected result:** a JSON object with a `types` array that includes `"snowflake"`, for example `{"types": ["bigquery", "clickhouse", "postgres", "snowflake", ...]}`. If `snowflake` is present, the next step's `config` shape is accepted.
{% endstep %}

{% step %}

### Create the Snowflake connector

`POST /v1/connectors` stores the connection name, type, and credentials, and returns the connector with `status: "untested"`. Fill in your real `account` (the Snowflake account identifier, such as `xy12345.eu-central-1`), `user`, `database`, and — recommended — a `warehouse` so queries have compute, plus an optional default `schema`.

```bash
curl -s -X POST "$ALGENTA_BASE_URL/v1/connectors" \
  -H "Authorization: Bearer $ALGENTA_API_KEY" \
  -H "Content-Type: application/json" \
  -d "{
    \"name\": \"Analytics Warehouse\",
    \"connector_type\": \"snowflake\",
    \"config\": {
      \"account\": \"xy12345.eu-central-1\",
      \"user\": \"ANALYTICS\",
      \"password\": \"$SNOWFLAKE_PASSWORD\",
      \"warehouse\": \"COMPUTE_WH\",
      \"database\": \"SALES\",
      \"schema\": \"PUBLIC\"
    }
  }"
```

If you already have a Snowflake DSN, pass it as `connection_string` instead of the structured fields — the engine reads either form:

```bash
curl -s -X POST "$ALGENTA_BASE_URL/v1/connectors" \
  -H "Authorization: Bearer $ALGENTA_API_KEY" \
  -H "Content-Type: application/json" \
  -d "{
    \"name\": \"Analytics Warehouse\",
    \"connector_type\": \"snowflake\",
    \"config\": {
      \"connection_string\": \"snowflake://ANALYTICS:$SNOWFLAKE_PASSWORD@xy12345.eu-central-1/SALES/PUBLIC?warehouse=COMPUTE_WH\"
    }
  }"
```

Capture the returned `id` for the steps that follow:

```bash
export CONNECTOR_ID="$CONNECTOR_ID"
```

**Expected result:** a `201` response with the connector `id`, `"connector_type": "snowflake"`, and `"status": "untested"`. Credentials are encrypted at rest — the connector object never returns your `config` back to you, only its name, type, status, and last test result.

{% hint style="warning" %}
The structured form requires `account`, `user`, `password`, and `database` together; if any is missing and no `connection_string` is given, the engine returns `422 missing_connection_string`. Provide a real `warehouse` — a role with no warehouse access surfaces a clear error at test time.
{% endhint %}
{% endstep %}

{% step %}

### Test the connection

`POST /v1/connectors/{id}/test` makes a real connection attempt — it logs in, activates the warehouse, and runs `SELECT CURRENT_VERSION()` — then flips the connector to `live` on success or `error` on failure. Browsing requires a `live` connector, so always test first.

```bash
curl -s -X POST "$ALGENTA_BASE_URL/v1/connectors/$CONNECTOR_ID/test" \
  -H "Authorization: Bearer $ALGENTA_API_KEY"
```

**Expected result:** `{"success": true, "status": "ok", "latency_ms": 312, "message": "Snowflake connection successful (xy12345.eu-central-1)"}`, and the connector's stored `status` is now `live`. On failure, `success` is `false`; `error_type` plus `recoverable` tell you whether to fix credentials and retry. An `error_type: "permission"` with a privacy-policy message means the account host is outside your deployment's egress allowlist.
{% endstep %}

{% step %}

### Browse the tables it exposes

`GET /v1/connectors/{id}/browse` lists the tables the live connector can see in its database and schema, so you can pick what to onboard. This returns `409 not_connected` if the connector is not `live` — run the test step first.

```bash
curl -s "$ALGENTA_BASE_URL/v1/connectors/$CONNECTOR_ID/browse" \
  -H "Authorization: Bearer $ALGENTA_API_KEY"
```

**Expected result:** a response with `"connector_type": "snowflake"`, an `items` array (each entry is a browsable table), a `total`, a `message`, and `discovery` metadata. Note the name of the table you want to query — for example `ORDERS`.
{% endstep %}

{% step %}

### Onboard one table as a dataset

`POST /v1/data/connect` ties the saved connector to a selection — a table or a SQL query — and registers the result as a queryable dataset. Reference the connector by `connection_id`, set `connection_type` to `database` and `provider` to `snowflake`, and name the table in `selection`.

```bash
curl -s -X POST "$ALGENTA_BASE_URL/v1/data/connect" \
  -H "Authorization: Bearer $ALGENTA_API_KEY" \
  -H "Content-Type: application/json" \
  -d "{
    \"connection_type\": \"database\",
    \"provider\": \"snowflake\",
    \"dataset_name\": \"sales_orders\",
    \"connection_id\": \"$CONNECTOR_ID\",
    \"selection\": {\"table\": \"PUBLIC.ORDERS\"},
    \"visibility\": \"private\"
  }"
```

To onboard a derived shape instead of a whole table, pass `selection` as a SQL query — for example `{"sql_query": "SELECT region, amount FROM PUBLIC.ORDERS"}`.

**Expected result:** when the selection identifies one table, `"status": "ready"` with a `dataset_id`, a `schema_summary` (row and column counts), and the `connection_id`. If the connection resolves to more than one table, you get `"status": "needs_selection"` with a `choices` array — re-call `/v1/data/connect` with the returned `connection_id` and one `selection` from `choices`. Save the `dataset_id`:

```bash
export DATASET_ID="$DATASET_ID"
```

{% endstep %}

{% step %}

### Run a governed query

The table is now governed data. `POST /v1/query` runs a deterministic, typed query against the dataset and returns rows under the engine's validated contract.

```bash
curl -s -X POST "$ALGENTA_BASE_URL/v1/query" \
  -H "Authorization: Bearer $ALGENTA_API_KEY" \
  -H "Content-Type: application/json" \
  -d "{
    \"dataset_id\": \"$DATASET_ID\",
    \"select\": [\"region\", \"amount\"],
    \"limit\": 10
  }"
```

**Expected result:** a `200` response with the matching rows and the resolved query plan. Re-running the same request against the same dataset returns the same rows in the same order — governed queries are deterministic by design.
{% endstep %}
{% endstepper %}

## Expected result

You have a saved `snowflake` connector with `status: "live"`, a browse listing of its tables, a dataset onboarded from one of them that appears in `GET /v1/data` with a `dataset_id` and a profiled schema, and a first query returning rows. The same intent against the same dataset returns the same deterministic answer, and every access is auditable.

## Other ways to connect

The same endpoints back the `de` CLI and the Python SDK — all three hit the identical API.

```bash
de connectors create connector.json     # POST /v1/connectors from a JSON body
de connectors test $CONNECTOR_ID         # real connection health check
de connectors browse $CONNECTOR_ID       # browse the live connector's tables
de data connect connect.json             # POST /v1/data/connect from a JSON body
de data list                             # list registered datasets
```

```python
import os
from decision_engine import AlgentaClient

client = AlgentaClient(
    api_key=os.environ["ALGENTA_API_KEY"],
    base_url="https://api.algenta.ai",
)

connector = client.create_connector(
    name="Analytics Warehouse",
    connector_type="snowflake",
    config={
        "account": "xy12345.eu-central-1",
        "user": "ANALYTICS",
        "password": os.environ["SNOWFLAKE_PASSWORD"],
        "warehouse": "COMPUTE_WH",
        "database": "SALES",
        "schema": "PUBLIC",
    },
)

test = client.test_connector(connector.id)
assert test.success, test.message

browse = client.browse_connector(connector.id)
print(browse.total, "tables")

result = client.connect_data(
    connection_type="database",
    provider="snowflake",
    dataset_name="sales_orders",
    connection_id=connector.id,
    selection={"table": "PUBLIC.ORDERS"},
    visibility="private",
)
print(result.status, result.dataset_id)
```

## Troubleshooting

{% hint style="warning" %}
**`422 missing_connection_string`.** The structured form is incomplete. Supply `account`, `user`, `password`, and `database` together, or pass a single `connection_string` DSN instead.
{% endhint %}

{% hint style="warning" %}
**`409 not_connected` when browsing.** The connector is not `live`. Run `POST /v1/connectors/{id}/test` first; only a connector that passes its test can be browsed.
{% endhint %}

{% hint style="warning" %}
**Test fails mentioning the warehouse is not accessible for the current role.** Grant warehouse usage to the login's role, or use a login permitted for a role with access to the `warehouse` you set. See [Authentication](/getting-started/authentication.md).
{% endhint %}

{% hint style="info" %}
**Test fails with `error_type: "permission"` or a privacy-policy message.** The Snowflake account host is outside the egress allowlist for your deployment. Confirm the `account` value and that the destination is permitted by your deployment's egress policy. See [Troubleshooting](/help/troubleshooting.md) for the full diagnosis flow.
{% endhint %}

## Next

{% content-ref url="/pages/1hWq4uaSOQ9pNlD9Ox0f" %}
[Query governed data](/guides/governed-query.md)
{% endcontent-ref %}

{% content-ref url="/pages/bxnYz4ESKz4Thr7Unlxd" %}
[Make your first query](/guides/first-query.md)
{% endcontent-ref %}

{% content-ref url="/pages/6eM92gJ0Ohzm1qrddkqr" %}
[BigQuery](/connectors/bigquery.md)
{% endcontent-ref %}


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