Source connector
Google Search Console connector
Google Search Console integration for databases, warehouses and BI tools
Organic search performance and indexing insights. Datrise captures Google Search Console entities such as queries, pages, impressions, clicks, and index coverage, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.
The Search Console API v1 (Search Analytics) authenticates with OAuth 2.0, service account, incremental runs key on date, and Google Search Console caps calls at Search Analytics: 1,200 queries/minute per site and per user, 40,000 QPM / 30,000,000 QPD per project; URL Inspection: 600 QPM / 2,000 QPD per site, 15,000 QPM / 10,000,000 QPD per project.
Of the 5 objects, 3 sync as upserts keyed on the primary key and 2 as append-only streams, so each incremental run moves only what changed since the last watermark. Every object lands in its own table (for example `google_search_console_queries`) with a schema derived from the Google Search Console API rather than a flattened CSV, in any of the 43 supported destinations.
Datrise is in early access: pick a destination below to open the Google Search Console pipeline page, and join the waitlist to get the Google Search Console connector (Ads) with guided onboarding.
What Google Search Console data Datrise extracts
Each object lands in its own typed table. Sync mode is derived from the object: history-style objects append, everything else upserts.
| Object | Landing table | Sync mode |
|---|---|---|
| queries | google_search_console_queries | Upsert by primary key, incremental on updated-at |
| pages | google_search_console_pages | Upsert by primary key, incremental on updated-at |
| impressions | google_search_console_impressions | Append-only, incremental by timestamp |
| clicks | google_search_console_clicks | Append-only, incremental by timestamp |
| index coverage | google_search_console_index_coverage | Upsert by primary key, incremental on updated-at |
Google Search Console API: setup facts for the connector
Verified against the vendor documentation on 2026-09-02. Unknown values are left blank rather than guessed.
| API | Search Console API v1 (Search Analytics) |
|---|---|
| Authentication | OAuth 2.0, service account — Standard Google OAuth 2.0 (user-consent) or a service account granted access to the property in Search Console; both use the usual Google API client libraries. |
| Pagination | offset — `searchanalytics.query` takes `startRow` and `rowLimit` (max 25,000 rows per request) and results are sorted by clicks, so exhausting a day's data means repeated calls incrementing `startRow`. |
| Rate limit | Search Analytics: 1,200 queries/minute per site and per user, 40,000 QPM / 30,000,000 QPD per project; URL Inspection: 600 QPM / 2,000 QPD per site, 15,000 QPM / 10,000,000 QPD per project |
| Incremental cursor | date — Query by the `date` dimension and re-pull the trailing few days on every run, since by default only "final" data is returned with a typical 2-3 day processing lag, while `dataState: all` exposes fresher rows that can still change before finalizing. |
| Webhooks | No |
| Bulk export | Yes — Bulk data export to BigQuery (daily scheduled export via a Google Cloud project, not subject to the 50K-rows/day API cap) |
| Deletes detectable | No |
What bites when replicating Google Search Console
- The Search Analytics API caps a query response at 25,000 rows and the whole day at roughly 50,000 rows per search type sorted by clicks, so long-tail queries and pages past that cutoff are simply unreachable through the API.
- Both the API and the Bulk Data Export drop "anonymized" low-volume/rare queries for privacy, so row counts will never reconcile exactly with what the Search Console UI shows for a property.
- Default responses return only finalized data with a roughly 2-3 day processing lag; requesting `dataState: all` returns fresher, unfinalized rows whose click/impression counts can still change on a later pull.
- The 1,200 queries/minute limit applies per site AND per user simultaneously, so a single credential polling many properties can be throttled well before any individual site's own limit is hit.
Popular destinations for Google Search Console
Choose a destination below to open the ready pipeline page.
- AAirtable
Relational spreadsheet destination for ops and go-to-market teams.
View pipeline - AAmazon Athena
Serverless SQL over S3 data lake tables.
View pipeline - AAmazon DynamoDB
Serverless key-value and document store on AWS.
View pipeline - AAmazon QuickSight
AWS serverless BI with SPICE and embedded analytics.
View pipeline - AAmazon Redshift
AWS petabyte-scale warehouse with Spectrum.
View pipeline - AAmazon S3 Data Lake
Object storage landing zone for parquet and snapshots.
View pipeline - AApache Superset
Open-source BI for SQL exploration, charts, and dashboard publishing.
View pipeline - AAzure Data Lake Storage
ADLS Gen2 object storage for analytics workloads.
View pipeline - AAzure Synapse
Microsoft analytics workspace with SQL pools.
View pipeline
Google Search Console connector FAQ
- What Google Search Console data does the connector extract?
- 5 objects: queries, pages, impressions, clicks and index coverage. Each lands in its own table with types preserved; history-style objects (2: impressions and clicks) load as append-only streams.
- Is the Google Search Console integration incremental?
- Yes. After the initial full load, every run reads only records changed since the last watermark (updated-at or event timestamp) and applies an upsert or an append depending on the object.
- Where can I load Google Search Console data?
- Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Google Search Console → destination pair has its own page with the object-to-table mapping.
Related Ads sources
Other sources in the same category, each with its own connector page.
Early access
Launch your Google Search Console pipeline with guided onboarding
Join the waitlist to get priority access for Google Search Console integrations with guided setup, schema-aware mapping, and production-grade incremental sync.