Marketing · Source connector
Taboola ELT Connector
Extract brings Taboola marketing data into data warehouses and databases for analysis with the rest of your business data. Teams use it to analyze campaign, creative, placement, spend, and revenue performance at a granular level. Flexible scheduling keeps reporting current for routine analysis and time-sensitive decisions.
View setup guide
Use cases
What teams use this connector for
Granular campaign optimization
Analyze Taboola campaign, creative, placement, geo, device, spend, and revenue detail to find opportunities to improve performance.
Direct-network reporting
Compare granular Taboola data with standard MMP and cost-aggregation reporting to work with dimensions those tools do not make available.
Spend and revenue reconciliation
Reconcile Taboola spend and revenue with finance, attribution, and internal performance data to investigate discrepancies.
Flexible performance monitoring
Refresh Taboola pacing, anomaly, and performance views every 15 minutes, hourly, daily, or on a custom schedule.
Warehouse and database analysis
Use Extract to make Taboola marketing data available in data warehouses and databases such as Snowflake, BigQuery, Redshift, and PostgreSQL for governed analysis.
Audience and campaign activation
Combine Taboola performance data with approved customer models, then use Extract Reverse ETL to activate audience or campaign updates downstream.
Connector data
Available streams
| Stream | Description | Sync mode |
|---|---|---|
campaign_summary_report_platform | Fields include account_id, campaign_id, date, platform. | Incremental |
campaign_summary_report_partner | Fields include account_id, campaign_id, date, campaigns_num. | Incremental |
children_items | Fields include account_id, campaign_id, id, item_id. | Full refresh |
accounts | Fields include id, account_id, campaign_types, currency. | Full refresh |
performance_video_item | Fields include account_id, campaign_id, id, approval_state. | Full refresh |
campaign_report_by_site | Fields include account_id, campaign_id, date, site_id. | Incremental |
campaign_report_by_campaign_by_smallest_time_bucket | Fields include account_id, campaign_id, date, campaign_name. | Incremental |
campaign_summary_report_country | Fields include account_id, campaign_id, country, country_name. | Incremental |
campaign_report_by_campaign | Fields include account_id, campaign_id, date, campaign_name. | Incremental |
ad_report_by_item | Fields include account_id, campaign_id, date, item_id. | Incremental |
campaign_items | Fields include account_id, campaign_id, id, approval_state. | Full refresh |
campaign_summary_report_site | Fields include account_id, campaign_id, date, site. | Incremental |
campaigns | Fields include account_id, id, activity_schedule.mode, activity_schedule.rules. | Full refresh |
ad_report_by_item_by_smallest_time_bucket | Fields include account_id, date, item_id, clicks. | Incremental |
campaign_report_by_site_by_smallest_time_bucket | Fields include account_id, campaign_id, date, site_id. | Incremental |
campaign_report_by_smallest_time_bucket | Fields include account_id, campaign_id, date, clicks. | Incremental |
Schema
Data model at a glance
campaign_summary_report_platform
account_idstringcampaign_idstringdatestringplatformstringplatform_namestringcampaigns_numintegerclicksnumberconversions_valuenumber
campaign_summary_report_partner
account_idstringcampaign_idstringdatestringcampaigns_numintegerclicksnumberconversions_valuenumbercpanumbercpa_actions_numinteger
children_items
account_idstringcampaign_idstringidstringitem_idstringapproval_statestringis_activebooleanstatusstringthumbnail_urlstring
accounts
idstringaccount_idstringcampaign_typesarraycurrencystringnamestringpartner_typesarraytime_zone_namestringtypestring
performance_video_item
account_idstringcampaign_idstringidstringapproval_statestringfallback_urlstringgif_urlstringis_activebooleanpolicy_review.reject_reasonstring
campaign_report_by_site
account_idstringcampaign_idstringdatestringsite_idstringclicksnumberconversions_valuenumbercpanumbercpa_actions_numnumber
No verified relationships are available in this schema preview.
Connector pairings
Popular destinations
Commonly paired with Taboola in Extract workflows.
Why Extract
Why Extract for Taboola
- Rust-native performanceUse Rust-native data movement to refresh Taboola reporting every 15 minutes, hourly, daily, or on a custom schedule as volume grows.
- Full run transparencyInspect Taboola API activity, execution steps, and timing in Extract's run-level logs when data needs review.
- ELT + Reverse ETL in oneCombine Taboola data with customer and finance models, then send approved outputs through a separately configured Reverse ETL destination.
FAQ
Frequently asked questions
How does Extract handle incremental and full Taboola syncs?
An incremental sync processes only new or changed data since a stored checkpoint or new date partition, while a full sync processes the complete selected dataset or date range again. By avoiding repeated processing and writes for the full dataset, incremental syncs can reduce destination database updates and warehouse compute costs. Stream schemas define full refresh, partition-based extraction. Behavior varies by stream and configuration. Extract records run details so teams can verify each sync.
Can I backfill historical Taboola data with Extract?
Historical coverage for Taboola: Backfill (Days) (backfill): The backfill setting revisits and updates data from the past X days, ensuring the most current and accurate information replaces any previously pulled data. Use the setup guide and run details to confirm the available source records and selected settings.
How can teams monitor Taboola data quality and freshness?
Compare expected reporting periods and record totals in your models, then use Extract's run-level logs to inspect Taboola API activity, execution steps, and timing. This helps teams distinguish a source-data delay from a failed or incomplete run.
How often can Extract sync data from Taboola?
Extract supports schedules every 15 minutes, hourly, daily, or on a custom cadence. Teams can choose a frequency that matches routine reporting, time-sensitive monitoring, or operational activation needs.
What does the Taboola data model look like in the destination?
The Available streams table describes the datasets Extract can read from Taboola. The inline schema previews entities and fields. Only relationships verified from the exported schema are shown. Use the full schema link for more details.