Load data into Google BigQuery in minutes

Source
Destination
Renta ELT — managed data loading into Google BigQuery. No data engineer, no custom scripts, no missed rows.

Google BigQuery is Google Cloud's serverless data warehouse built for fast analytics across terabytes and petabytes of data.

Renta turns BigQuery into your single source of truth by automatically pulling data from 100+ sources — ad platforms, CRMs, databases and SaaS tools — normalizing the schema and writing ready-to-query tables.

Marketing, product and data teams can focus on dashboards, attribution models and ML forecasts instead of maintaining homegrown ETL scripts.

Start loading data into BigQuery in 3 steps

Pick any connector — ad platforms, CRMs, databases, SaaS — and authorize the account in a couple of clicks. No code, no servers to maintain.

Connecting a data source in Renta for loading into Google BigQuery.
1Connect a source

Pick any connector — ad platforms, CRMs, databases, SaaS — and authorize the account in a couple of clicks. No code, no servers to maintain.

Connecting a data source in Renta for loading into Google BigQuery.
2Choose Google BigQuery
3Configure and sync
BigQuery loading capabilities

Renta replicates data into BigQuery with production-grade reliability — typed, normalized and backed by a 99.9% SLA.

Incremental sync

After the initial historical backfill Renta only writes new and changed records to BigQuery. This reduces storage cost, source load and refresh latency — from 15-minute windows down to daily.

Automatic schema

Renta creates tables, assigns column types and tracks schema changes on the source side. When a new field appears in the API, a column is added to BigQuery without breaking the pipeline.

Typing and normalization

Data types from every source are normalized to a single consistent format. Cross-source JOINs work without manual CAST or JSON parsing.

Upsert and deduplication

Renta uses a MERGE strategy and the source's natural keys to prevent duplicates in BigQuery. Records are updated by primary key, deletes are soft-flagged and retroactive changes are applied correctly.

Use cases

What teams build on top of BigQuery data

  • Join GA4, ad platform and CRM data in BigQuery to compute end-to-end CAC, LTV and ROMI per channel
  • Build attribution models (last-click, data-driven, Markov) on raw events and spend replicated by Renta
  • Train ML models in BigQuery ML directly on Renta tables — churn, LTV and conversion propensity forecasts
  • Visualize data in Looker Studio, Power BI and Tableau straight from BigQuery, with no manual exports
  • Blend financial data from Stripe, Paddle and billing databases with marketing spend for cohort-level P&L
  • Run freshness monitoring and business alerts on top of BigQuery tables — Renta refreshes as often as every 15 minutes
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Google BigQuery use cases powered by Renta data
Frequently asked questions
Launch analytics on Google BigQuery today

Free for 7 days. No credit card required.

Automated data collection. 99.9% SLA.