The extraction landscape for advertising data splits into three tiers based on how much engineering time you trade for money. The right choice depends on team size, number of ad platforms, budget, and tolerance for maintenance work.
Managed ELT Tools
Managed tools handle API authentication, pagination, rate limiting, schema changes, and error handling for you. You configure a connection, point it at your warehouse, and data flows.
Fivetran — managed ELT, 700+ connectors. Pricing from ~$500/month based on monthly active rows. Mature ad-platform connectors (Google Ads, Meta, LinkedIn). Companion dbt_ad_reporting package provides pre-built transformation models. Trade-off: highest cost, lowest maintenance burden; API-change handling (schema migrations, auth token rotation) is included.
Airbyte Cloud — credit-based pricing at $2.50 per credit. Ad-platform connectors vary in maturity: Google Ads and Meta are solid; less popular platforms may be community-maintained with alpha-level stability. Lower price point than Fivetran; trade-off is less consistent connector quality.
Supermetrics — connects ad platforms to Google Sheets, Looker Studio, or a warehouse. Targeted at non-technical marketing teams. Less flexible for complex transformations; limited integration with dbt-based workflows.
Funnel.io — can serve as a marketing data warehouse with built-in data mapping and normalization. Some teams use Funnel for marketing data and sync only the normalized output to a central warehouse. Creates a data silo if other teams need direct access.
Open-Source and Code-First Options
Open-source tools trade subscription costs for engineering time. You get full control and zero licensing fees, but you own the maintenance.
dlt — Python library with declarative REST API connectors, automatic schema evolution, and built-in dbt integration. pip-installable, no Docker required, runs anywhere Python runs (locally, in Airflow, in a cloud function). Well-suited for Python-heavy teams managing one or two ad platforms.
Airbyte OSS — Docker-based self-hosted option with 600+ connectors. Many connectors are community-maintained and vary from production-ready to alpha quality. Running Airbyte OSS requires managing Docker containers, a metadata database, and the Airbyte platform itself.
Meltano — CLI-first orchestrator with 300+ Singer connectors (taps and targets). The Singer ecosystem is aging but stable. Meltano adds configuration management and scheduling. Suited for lightweight, git-controlled extraction pipelines.
Custom Python scripts — maximum control at the highest maintenance cost. Requires writing API calls, pagination logic, rate limit handling, schema mapping, and error recovery. Simpler than installing a platform for a single source; maintenance burden typically exceeds what a small team can sustain across three or more platforms.
Native Integrations
Some platforms offer direct warehouse integrations that bypass the need for a separate extraction tool.
The Google Ads BigQuery Data Transfer Service is free, runs daily, and produces a fixed schema in your BigQuery project. Setup takes minutes. Limitations: daily granularity only (no intraday refreshes), a fixed schema, and well-documented gaps with Performance Max campaigns. The simplest option for Google Ads data at daily grain.
Choosing the Right Tier
Key decision factors:
- Platform count. One or two platforms can be managed with open-source tools or custom scripts. Three or more platforms increase maintenance surface area (API changes, auth token rotation, rate limit tuning) enough to favor managed tools.
- Engineering capacity. Teams with dedicated data engineers can sustain open-source pipelines. Solo analytics engineers or marketing-led teams benefit from managed reliability.
- Budget. Fivetran at $500+/month is significant at small scale; at $50K+/month in ad spend, the engineering time saved typically exceeds the subscription cost.
- Data freshness. Native integrations (BigQuery DTS) are daily. Managed tools typically offer hourly or 6-hour sync cadences. Near-real-time requirements usually require direct API integration regardless of other choices.
Trends
The dbt Labs + Fivetran merger (announced early 2026) signals deeper integration between ingestion and transformation layers. The dbt_ad_reporting package is already the most popular dbt package for marketing data; tighter coupling between connectors and transformation packages is expected.
Composable CDPs: teams are building audiences directly in BigQuery or Snowflake and syncing them to ad platforms via reverse ETL tools — Hightouch, Census, DinMo. Extraction (into the warehouse) and activation (pushing data back to ad platforms) are both parts of the stack.