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Snowflake (Deprecated)

Note: this solution is still functional, but can be manual and time consuming to set up with minimal error handling. We encourage you to check out the Data Warehouse Ingestion solution instead.


There are 2 ways to integrate with Snowflake: using a data connector, or through direct ingestion from Snowflake.

Using a Data Connector

To ingest events from Snowflake, you can use our Census integration.

To export events to Snowflake, you can use our Fivetran integration.

Direct ingestion from Snowflake

We also support direct data ingestion from Snowflake, through which Statsig will automatically pull data from Snowflake into your events. You will need to do the following steps. Please follow the checklist to avoid delays!

1. Set up your Snowflake data warehouse and user for Statsig integration

Insert USER and PASSWORD values to the below and run it in a Snowflake worksheet on an account which has sysadmin and securityadmin roles.

This will create the table schemas and setup that Statsig's ingestion will use. Statsig will use the user you create to access tables in the new Statsig schema. Make sure to use a unique and secure username and password and replace the placeholder values in the first 2 statements.


-- set up variable values to be used in statements later
-- make sure to configure user_name and user_password with your own values
SET role_name = 'STATSIG_ROLE';

-- change role to sysadmin for warehouse / database steps
USE ROLE sysadmin;

-- create a warehouse, database, schema and tables for Statsig

-- a table for ingestion of raw events
CREATE TABLE IF NOT EXISTS statsig.statsig.statsig_events(
time BIGINT NOT NULL, -- unix time
timeuuid STRING NOT NULL DEFAULT UUID_STRING(), --generated unique timeuuid
user STRING NOT NULL, --json user object
event_name STRING NOT NULL,
event_value STRING,
event_metadata STRING NOT NULL, --json metadata object
event_version BIGINT,

-- a table for ingestion of metrics/user outcomes
CREATE TABLE IF NOT EXISTS statsig.statsig.statsig_user_metrics(
id_type STRING NOT NULL, -- stable_id, user_id, etc.
date DATE NOT NULL, -- YYYY-MM-DD. Statsig calculates dates according to PST
metric_name STRING NOT NULL,
metric_value NUMBER,
numerator NUMBER,
denominator NUMBER

CREATE TABLE IF NOT EXISTS statsig.statsig.statsig_events_signal(
finished_date DATE

CREATE TABLE IF NOT EXISTS statsig.statsig.statsig_user_metrics_signal(
finished_date DATE

-- change current role to securityadmin to create role and user for Statsig's access
USE ROLE securityadmin;

-- create role for Statsig
CREATE ROLE IF NOT EXISTS identifier($role_name);
GRANT ROLE identifier($role_name) TO ROLE SYSADMIN;

-- create a user for Statsig
CREATE USER IF NOT EXISTS identifier($user_name)
password = $user_password
default_role = $role_name
default_warehouse = statsig;
GRANT ROLE identifier($role_name) TO USER identifier($user_name);

-- grant Statsig role access
GRANT USAGE ON WAREHOUSE statsig TO ROLE identifier($role_name);
GRANT USAGE ON DATABASE statsig TO ROLE identifier($role_name);
GRANT USAGE ON SCHEMA statsig.statsig TO ROLE identifier($role_name);
GRANT SELECT ON statsig.statsig.statsig_events TO ROLE identifier($role_name);
GRANT SELECT ON statsig.statsig.statsig_user_metrics TO ROLE identifier($role_name);
GRANT SELECT ON statsig.statsig.statsig_events_signal TO ROLE identifier($role_name);
GRANT SELECT ON statsig.statsig.statsig_user_metrics_signal TO ROLE identifier($role_name);


Make sure all the statements ran successfully. This will create the schema and user that Statsig's ingestion expects.

2. Provide the credentials to Statsig

  • Go to and log in
  • Go to the settings page and navigate to the integrations tab.
  • Find Snowflake in the integrations list and provide the requested credentials for the user you just created in step 1.
  • You can use the "Test Connection" button to make sure we can establish a connection to the table using the credentials provided.


3. Load data into the new Statsig tables

In step 1 we created 2 data tables and 2 signal tables. To load data into statsig, you will load data into the data tables, and mark a day as completed in the corresponding signal table once all of the data for that day is loaded.

The statsig_events table is for sending Statsig raw events which were not logged to Statsig through the API. Once loaded, these events will be processed as though they were logged directly.

The statsig_user_metrics table is for sending pre-computed metrics from your data warehouse. These metrics will be surfaced in the statsig console and in your test results.

You may only need one of these use cases - that's fine! Just follow the steps for the relevant table and ignore the other one.

Your data should conform to these definitions and rules to avoid errors or delays:

Events (statsig_events)

timeThe unix time your event was logged atNot null
timeuuidA unique timeuuid for the eventThis should be a timeuuid, but using a unique id will suffice. If not provided, the table defaults to generating a UUID.
userA user json object.See below
event_nameThe name of the eventNot null. Length < 128 characters
event_valueThe value of the eventLength < 128 characters
event_metadataMetadata about the eventNot null. Length < 16384 characters. Json-formatted - leave empty if none
event_versionThe version of this event

The user object is a stringified JSON representation. An example might look like:

"os": "Mac OS X",
"os_version": "10.15.7",
"browser_name": "Electron",
"browser_version": "11.5.0",
"ip": "",
"country": "KR",
"locale": "en-US",
"userID": "bbbbb-bbbbb-bbbbb-bbbbb",
"custom": {
"locale": "en-US",
"clientVersion": "",
"desktopVersion": "11.5.0"
"customIDs": {
"deviceId": "ddddd-ddddd-ddddd-ddddd",
"stableID": "sssss-sssss-sssss-sssss"

Key components of the user object are the userID, custom fields, and the customIDs object (notably stableID) if you are using any custom identifiers.

Make sure these fields are provided where they exist, and that the names of the fields capitalized correctly. Not providing a unit identifier will limit the utility of your events, as we won't be able to use them to build metrics like daily event users.

Metrics (statsig_user_metrics)

unit_idThe unique user identifier this metric is for. This might not necessarily be a user_id - it could be a custom_id of some kind
id_typeThe id_type the unit_id represents.Must be a valid id_type. The default Statsig types are user_id/stable_id, but you may have generated custom id_types
dateDate of the daily metric
timeuuidA unique timeuuid for the eventThis should be a timeuuid, but using a unique id will suffice. If not provided, the table defaults to generating a UUID.
metric_nameThe name of the metricNot null. Length < 128 characters
metric_valueA numeric value for the metricMetric value, or both of numerator/denominator need to be provided for Statsig to process the metric. See details below
numeratorNumerator for metric calculationSee above, and details below
denominatorDenominator for metric calculationSee above, and details below

Metric ingestion is for user-day metric pairs. This is useful for measuring experimental results on complex business logic (e.g. LTV estimates) that you generate in your data warehouse.

Note on metric values

If you provide both a numerator and denominator value for any record of a metric, we'll assume that this metric is a ratio metric; we'll filter out users who do not have a denominator value from analysis, and recalculate the metric value ourselves via the numerator and denominator fields.

If you only provide a metric_value, we'll use the metric_value for analysis. In this case, we'll impute 0 for users without a metric value in experiments.


Because you may be streaming events to your tables or have multiple ETLs pointing to your metrics table, Statsig relies on you signalling that your metric/events for a given day are done.

When a day is fully loaded, insert that date as a row in the appropriate signal_table - statsig_user_metrics_signal for metrics or statsig_events_signal for events. For example, once all of your metrics data is loaded into statsig_user_metrics for 2022-04-01, you would insert 2022-04-01 into statsig_user_metrics_signal.

Statsig expects you to load data in order. For example, if you have loaded up to 2022-04-01 and signal that 2022-04-03 has landed, we will wait for you to signal that 2022-04-02 has landed, and load that data before we ingest data from 2022-04-03

NOTE: this ingestion pipeline is in beta, and does not currently support automatic backfills or updates to data once it's been ingested. Only signal these tables are loaded after you've run data quality checks!


These are common errors we've run into - please go through and make sure your setup is looking good!

  • Field names are set incorrectly
    • Some of the field names here may intersect with protected key words. You should be able to generate these by wrapping them in quotes if needed. The above SQL works in the snowflake console.
    • Run SELECT * on your tables when done to confirm that there aren't any special characters in the column names! This will cause our ingestion to fail.
  • The id_type is set correctly
    • Default types are user_id or stable_id. If you have custom ids, make sure that the capitalization and spelling matches as these are case sensitive (you can find your custom ID types by going to your Project Settings in the Statsig console).
  • Your ids match the format of ids logged from SDKs
    • In some cases, your data warehouse may transform IDs. This may mean we can't join your experiment or feature gate data to your metrics to calculate pulse or other reports. You can go to the Metrics page of your project and view the log stream to check the format of the ids being sent (either User ID, or a custom ID in User Properties) to confirm they match

If your data is not showing up in the Statsig console

  • Monitoring is limited today, but you should be able to check your snowflake query history for the Statsig user to understand which data is being pulled, and if queries are not executing (no history) or are failing.
  • You should see polling queries within a few hours of setting up your integration.
  • If you have a signal date in the last 28d, you should see a select statement for data from the earliest signal date in that window
  • If that query fails, try running it yourself to understand if there is a schema issue
  • If data is loading, it's likely we're just processing. For new metrics, give it a day to catch. If data isn't loaded after a day or two, please check in with us. The most common reason for metrics catalog failures is due to id_type mismatches.