Home > Destinations > PostgreSQL > AppsFlyer

Connect AppsFlyer to PostgreSQL

Connect AppsFlyer to PostgreSQL and export selected accounts, metrics, and dimensions to your PostgreSQL project.

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

AppsFlyer export job

First sync scheduled

AppsFlyer Selected accounts

Configured job

PostgreSQL Destination table

Account AppsFlyer · 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 AppsFlyer data to PostgreSQL

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize AppsFlyer data in PostgreSQL

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

Source

AppsFlyer Advertising data

INapps PMcampaigns CUad_groups BLads

Catchr pipeline IN PM CU Extract · normalize · load

PostgreSQL catchr_data.AppsFlyer_raw

TableScopeStatus

appsSelectedReady

campaignsSelectedReady

ad_groupsSelectedReady

adsSelectedReady

Data freshness

Keep your PostgreSQL tables up to date

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

AppsFlyerConfigured account

PostgreSQLAppsFlyer 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

apps326 updated campaigns102 appended Warehouse up to date

Analysis

Unify AppsFlyer 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 apps · Activity Average DAU Advertising

Marketingcampaign · spend · UTM Ads

CRMcontact_id · lifecycle Sales

Productaccount_id · event_date Usage

Match keys customer · date · campaign

PostgreSQL model business_360 Unified

FieldFrom

customer_idCRM

Activity Average DAUapps

ad_spendMarketing

lifecycle_stageCRM

active_usersProduct

Ready for SQL 5 business fields

AppsFlyer metrics and dimensions available in PostgreSQL

Access 40 metrics and 140 dimensions from AppsFlyer connectors including Revenue, Cost, Installs, ROI, Conversion Rate, AF Purchase (Unique Users), Campaign, Media Source, Channel, App Name, Country Code, Date and many more...

Metrics availables

140

Dimensions availables

View all AppsFlyer Metrics metrics and dimensions

Connect AppsFlyer to PostgreSQL in minutes

Move your data from AppsFlyer to PostgreSQL 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 AppsFlyer account

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

Connect now

Client A · Connected sources

5 sources ready

AppsFlyer 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 PostgreSQL destination

Add the database host and credentials once. Catchr checks the connection so your exports start with a reachable destination.

Destination / PostgreSQL Required fields

Host Required

warehouse.company.net

Username Required

catchr_writer

Password Required

••••••••••••

Database Required

marketing

Step three

Keep your PostgreSQL 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 AppsFlyer mobile acquisition performance in SQL.

This example summarizes spend, installs, revenue, and cost per install by acquisition campaign.

30-day window

SELECT
  campaign_name,
  SUM(spend) AS spend,
  SUM(installs) AS installs,
  SUM(revenue) AS revenue,
  SAFE_DIVIDE(
    SUM(spend),
    SUM(installs)
  ) AS cost_per_install
FROM `your_project.marketing_raw.appsflyer_daily`
WHERE date >= DATE_SUB(
  CURRENT_DATE(),
  INTERVAL 30 DAY
)
GROUP BY campaign_name
ORDER BY installs DESC;

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

Choose what to load into PostgreSQL.

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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Finance

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 AppsFlyer data to PostgreSQL?

Add AppsFlyer in Sources and connect the existing PostgreSQL database in Storage. A datastream defines the route, while the job loads the chosen fields into "creatives".

What can I select from AppsFlyer before writing to PostgreSQL?

Select concrete AppsFlyer fields such as Activity Average DAU, Activity Average DAU/MAU Rate, Activity Average MAU, and Normalized Week of the year. You can rename the chosen columns, preview the result, and write them to PostgreSQL tables such as apps, campaigns, and ad groups.

Can an AppsFlyer-to-PostgreSQL job import historical periods?

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

Why does the AppsFlyer PostgreSQL job need a partition field?

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

Which decisions can an AppsFlyer dataset in PostgreSQL support?

With AppsFlyer data, a PostgreSQL query can summarize spend, installs, revenue, and cost per install by acquisition campaign. Model Activity Average DAU and Activity Average DAU/MAU Rate in SQL, then expose the result to dashboards, internal tools, or recurring client reports.

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

Yes. Connect an existing PostgreSQL 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 Postgres 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 ?

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100+ sources

Used by the world's leading companies

Export AppsFlyer data to PostgreSQL

Centralize AppsFlyer data in PostgreSQL

Keep your PostgreSQL tables up to date

Unify AppsFlyer with the rest of your business data

AppsFlyer metrics and dimensions available in PostgreSQL

Connect AppsFlyer to PostgreSQL in minutes

Connect your AppsFlyer account

Choose the PostgreSQL destination

Keep your PostgreSQL tables updated

Review 30-day AppsFlyer mobile acquisition performance in SQL.

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