Twitter Ads to DuckDB Integration

How Datrise loads Twitter Ads into DuckDB

Datrise syncs Twitter Ads's campaigns, line items, promoted tweets, spend, impressions, and conversions into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

Twitter Ads: Paid campaign delivery and performance on X.

DuckDB: In-process analytics database for fast local OLAP.

How Twitter Ads entities map to DuckDB

Twitter Ads entity	DuckDB object	Notes
campaigns	`twitter_ads_campaigns`	id PK · custom fields → JSON or STRUCT columns
line items	`twitter_ads_line_items`	id PK · linked to twitter_ads_campaigns
promoted tweets	`twitter_ads_promoted_tweets`	id PK · linked to twitter_ads_campaigns
spend	`twitter_ads_spend`	id PK · linked to twitter_ads_campaigns

FAQ

How does Datrise handle Twitter Ads's custom fields in DuckDB?

Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.

How does the Twitter Ads to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

Early access

Connect Twitter Ads to DuckDB the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.