DatriseAI-first ETL

Meta Ads Amazon S3 Data Lake

AI-first ETL from Meta Ads into Amazon S3 Data Lake. Governed entities, incremental sync, typed landing tables.

How Datrise loads Meta Ads into Amazon S3 Data Lake

Datrise syncs Meta Ads's campaign spend, impressions, clicks, conversions, and audience segments into Amazon S3 Data Lake as columnar Parquet objects partitioned per source entity. Flexible or custom fields land in nested struct/map fields in Parquet, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.

Sync is incremental: Datrise uses writes new date partitions and compacts small files on a schedule, so re-runs update only what changed. Hive-style path partitioning (entity/date) for engine-agnostic reads. A lake has no schema enforcement, so Datrise writes a schema manifest alongside the data to keep downstream engines consistent.

Ideal for an open, engine-neutral storage layer for Spark, Athena, Trino, or DuckDB.

Endpoints

Meta Ads: Facebook and Instagram ad source for spend and engagement.

Amazon S3 Data Lake: Object storage landing zone for parquet and snapshots.

How Meta Ads entities map to Amazon S3 Data Lake

Meta Ads entityAmazon S3 Data Lake objectNotes
campaign spendmeta_ads_campaign_spendid PK · custom fields → nested struct/map fields in Parquet
impressionsmeta_ads_impressionsid PK · linked to meta_ads_campaign_spend
clicksmeta_ads_clicksid PK · linked to meta_ads_campaign_spend
conversionsmeta_ads_conversionsid PK · linked to meta_ads_campaign_spend

FAQ

How does Datrise handle Meta Ads's custom fields in Amazon S3 Data Lake?

Flexible values are stored as nested struct/map fields in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon S3 Data Lake types.

How does the Meta Ads to Amazon S3 Data Lake sync stay up to date?

It runs incrementally — Datrise uses writes new date partitions and compacts small files on a schedule.

Related pipelines

Early access

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