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Connect Braze to Snowflake

Connect Braze to Snowflake and export selected accounts, metrics, and dimensions to your Google BigQuery project.

Configure the historical window, destination table, and recurring schedule without maintaining a Braze API pipeline.

Braze export job

First sync scheduled

Braze Selected accounts

Configured job

Snowflake Destination table

Account Braze · Client group A

Table daily_dump

Initial import Configured historical window

Schedule Daily · 06:00 UTC

Fields Selected metrics + dimensions

Partition date · eligible field

Illustrative job · configure values for your account Export ready

Used by the world's leading companies

Export Braze data to Snowflake

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Braze data in PostgreSQL

Bring all your Braze data into your warehouse and make it available for analytics, machine learning, and internal applications.

Source

Braze CRM data

INaccounts PMcampaigns CUcontacts BLlists

Catchr pipeline IN PM CU Extract · normalize · load

Snowflake catchr_data.Braze_raw

TableScopeStatus

accountsSelectedReady

campaignsSelectedReady

contactsSelectedReady

listsSelectedReady

Data freshness

Keep your Snowflake tables up to date

Automatically sync new data from Braze so every dashboard, model, and report works with fresh information.

BrazeConfigured account

SnowflakeBraze Metrics_raw

Rows processed Scheduled loads Example 24h

00:0006:0012:0018:00

Latest run Completed 06:00 UTC

New rows +428 4 tables updated

Next run Scheduled 12:00 UTC

accounts326 updated campaigns102 appended Warehouse up to date

Analysis

Unify Braze with the rest of your business data

Join marketing, finance, CRM, and product data inside the same warehouse.

Business data model

model / business_360

Warehouse inputs

QuickBooks accounts · Campaign Message Channel CRM

Marketingcampaign · spend · UTM Ads

CRMcontact_id · lifecycle Sales

Productaccount_id · event_date Usage

Match keys customer · date · campaign

Snowflake model business_360 Unified

FieldFrom

customer_idCRM

Campaign Message Channelaccounts

ad_spendMarketing

lifecycle_stageCRM

active_usersProduct

Ready for SQL 5 business fields

Braze metrics and dimensions available in Snowflake

Access 40 metrics and 78 dimensions from Braze connectors including Sent, Delivered, Opens, Unique Clicks, Conversions, Revenue, Unique Recipients, Daily Active Users, Date, Campaign Name Summary, Campaign Detail Channel, Canvas Name Summary, Step Name, Segment Name Summary, Event Name, Campaign Tag Value and many more...

Metrics availables

Dimensions availables

View all Braze Metrics metrics and dimensions

Connect Braze to Snowflake in minutes

Move your data from Braze to Snowflake with a simple setup. Once connected, Catchr handles the ingestion automatically so your warehouse stays up to date without manual work.

Step one

Connect your Braze account

Authenticate your Braze account securely in Catchr. No custom scripts, API maintenance, or engineering work required.

Connect now

Client A · Connected sources

5 sources ready

Braze 3 advertising accounts Connected

Google Ads 2 advertising accounts Connected

Google Analytics 4 1 web property Connected

HubSpot 1 CRM portal Connected

Step two

Choose the Snowflake destination

Add the account host, user, and database schema. Use a password for compatible users or a PEM private key for service accounts and stricter policies.

Destination / Snowflake Required fields

Authentication Choose one

Password

Key pair

Host Required

xy12345.eu-west-1

Username Required

catchr_service

Database Required

MARKETING.RAW

Private key passphrase Optional

••••••••••••

Private key Required for key pair

-----BEGIN ENCRYPTED PRIVATE KEY----- MIIE6TAbBgkqhkiG9w0BBQMw... -----END ENCRYPTED PRIVATE KEY-----

Step three

Keep your Snowflake tables updated

Choose the fields, initial history, partition field, and recurring schedule for the job. Catchr refreshes the configured import window in your PostgreSQL table.

Export job / PostgreSQL Example

Schema Destination

marketing_raw

Table Per job

linkedin_ads_daily

Recurring schedule Choose a cadence

Every 6 hours

Daily · 07:00

Weekly · Mon

First sync scheduledSelected fields · configured history

07:00 UTC

Review 30-day Braze email campaign performance in SQL.

This example summarizes delivery, opens, clicks, and engagement rates by email campaign.

30-day window

SELECT
  campaign_name,
  SUM(sent) AS sent,
  SUM(delivered) AS delivered,
  SUM(opens) AS opens,
  SUM(clicks) AS clicks,
  SAFE_DIVIDE(
    SUM(opens),
    SUM(delivered)
  ) AS open_rate,
  SAFE_DIVIDE(
    SUM(clicks),
    SUM(delivered)
  ) AS click_rate
FROM `your_project.marketing_raw.braze_campaign_daily`
WHERE date >= DATE_SUB(
  CURRENT_DATE(),
  INTERVAL 30 DAY
)
GROUP BY campaign_name
ORDER BY delivered DESC;

Illustrative SQL — adapt it to the fields and schema selected in your export. Standard SQL

Choose what to load into Snowflake.

Each connector has its own entities, fields, historical limits, and reporting uses. Open a source page for the details that belong to that platform.

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Emailing

Before you schedule the job.

Answers about PostgreSQL setup, available source data, schedules, table updates, and SQL use cases.

What is the setup for sending Braze data to Snowflake?

Add Braze in Sources and connect the existing Snowflake database in Storage. A datastream defines the route, while the job loads the chosen fields into "lists".

What can I select from Braze before writing to Snowflake?

Select concrete Braze fields such as Campaign Message Channel, Clicks, Conversions, and Day of the month. You can rename the chosen columns, preview the result, and write them to Snowflake tables such as accounts, campaigns, and contacts.

Can a Braze-to-Snowflake job import historical periods?

Define the first Braze fetch, run frequency, and lookback window in the "lists" job. Each scheduled run replaces data inside the configured period.

Why does the Braze Snowflake job need a partition field?

Use a supported date field to partition "lists". Recurring Braze runs can then update the selected window instead of adding another copy of the same period.

Which decisions can a Braze dataset in Snowflake support?

With Braze data, a Snowflake query can summarize delivery, opens, clicks, and engagement rates by email campaign. Model Campaign Message Channel and Clicks in SQL, then expose the result to dashboards, internal tools, or recurring client reports.

Does my Snowflake database need to exist before I connect it?

Yes. Connect an existing Snowflake database first. The Catchr job creates and populates the destination table you configure inside that database.

Can I load several marketing sources into the same Snowflake database?

Yes. Create a separate datastream and job for each source, write each export to its own table, then combine the data downstream with SQL, views, or your BI tool.

Still have a question ?

Our teams is always here to responds to any question you could have about our data connector.

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100+ sources

Used by the world's leading companies

Export Braze data to Snowflake

Centralize Braze data in PostgreSQL

Keep your Snowflake tables up to date

Unify Braze with the rest of your business data

Braze metrics and dimensions available in Snowflake

Connect Braze to Snowflake in minutes

Connect your Braze account

Choose the Snowflake destination

Keep your Snowflake tables updated

Review 30-day Braze email campaign performance in SQL.

Choose what to load into Snowflake.

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