If you’ve ever struggled to get the full picture from your Google Analytics 4 (GA4) reports, you’re not alone. While GA4 offers powerful insights through its event-based model, getting raw, unsampled data into a scalable environment for deep analysis has been a challenge—until now.

Google has just launched a new native GA4 to BigQuery connector that automates the export of aggregated GA4 report data to BigQuery. This development is significant, especially for marketers and analysts seeking smoother access to GA4 insights in the cloud. But here’s the catch: while Google’s solution is a big step forward, it still has limitations that might hold you back from advanced data use cases.

Let’s dive into what this new GA4 to BigQuery connector offers and how it compares to Dataslayer.

• New Google GA4 to BigQuery Connector
  • Key Features
• The Native Export: Raw Power with Rough Edges
• Why Dataslayer Is a Smarter Way to Move GA4 Data to BigQuery
  • Why Dataslayer instead of the native GA4 connector?
    • Historical Data Import
    • Multiple Marketing Data Sources
    • Flexible Data Refresh Scheduling
    • No-Code Simplicity
    • Scalable & Cost-Effective Plans
• GA4 to BigQuery: Feature-by-Feature Comparison
• Who Should Choose What?
  • Go with Google’s Native Export if:
  • Choose Dataslayer if:
• Final Verdict: Raw Data vs. Real Efficiency
  • Ready to simplify your GA4 data automation?

New Google GA4 to BigQuery Connector

Google has launched a new native connector that allows users to schedule automatic transfers of pre-aggregated GA4 report data directly into BigQuery. This update significantly streamlines the GA4 to BigQuery workflow, giving marketing teams easier access to aggregated analytics in a scalable, queryable environment without needing to export manually or build custom scripts.

Key Features

• Predefined GA4 reports: Automatically exported.
• Daily and streaming export options: Streaming data incurs extra costs.
• No backfilling of historical data prior to the setup date.
• Requires technical setup through Google Cloud Platform and GA4 admin access.

At first glance, this GA4 to BigQuery integration seems ideal for real-time reporting and granular analysis. But once you dig deeper, limitations surface—especially for non-technical teams or those needing more flexible, customized solutions.

The Native Export: Raw Power with Rough Edges

While Google's native GA4 to BigQuery export gives you event-level data, it comes with notable drawbacks:

• No support for importing historical data (a deal-breaker for many).
• Requires SQL and BigQuery knowledge to query nested data tables.
• Daily event limit of 1 million for standard GA4 properties.
• No integrations beyond GA4—meaning siloed data.

If your team lacks SQL skills or needs a more user-friendly interface, this can quickly become more of a burden than a benefit.

Why Dataslayer Is a Smarter Way to Move GA4 Data to BigQuery

Dataslayer offers a different approach: a no-code platform designed for marketers and analysts to automate GA4 to BigQuery data transfers (and other platforms)—without writing a single line of SQL.

Why Dataslayer instead of the native GA4 connector?

Historical Data Import

Unlike Google’s native connector, Dataslayer may allow backfilling GA4 historical data via the API, depending on data availability and API permissions. This means you don’t lose critical insights from before your export was set up.

Multiple Marketing Data Sources

Dataslayer connects not just to GA4, but also to platforms like Facebook Ads, Google Ads, HubSpot, and more—enabling a centralized marketing data warehouse in BigQuery.

Flexible Data Refresh Scheduling

You can configure exports hourly, daily, weekly, etc., ensuring your BigQuery tables stay fresh without the overhead of streaming costs.

No-Code Simplicity

No need for BigQuery expertise or complex SQL. With Dataslayer, you just link your accounts, schedule your refreshes, and your GA4 to BigQuery pipeline is ready to go.

Scalable & Cost-Effective Plans

Dataslayer offers flexible pricing based on API usage and data volume, often more affordable than alternatives like Supermetrics, especially for mid-sized teams or agencies.

GA4 to BigQuery: Feature-by-Feature Comparison

FeatureGoogle Native ExportDataslayerData TypeRaw, event-levelAggregated (API-based)Historical Data Import❌ Not supported✅ SupportedReal-Time Export✅ Streaming (extra cost)⏳ Scheduled (hourly/daily)Ease of UseRequires BigQuery & SQLNo-code, user-friendlyMulti-Platform Integration❌ GA4 only✅ Yes (Google Ads, Meta, etc.)PricingFree (usage fees apply)Subscription-based, flexible

Who Should Choose What?

Go with Google’s Native Export if:

• You need raw, unsampled event data.
• You have an in-house team skilled in SQL and BigQuery.
• Your GA4 data volume is moderate and fits within the free tier.

Choose Dataslayer if:

• You need to import historical data from GA4.
• You want to combine GA4 with other marketing data sources in BigQuery.
• You prefer a no-code solution that doesn’t require BigQuery expertise.
• You need easy scheduling and automated workflows.
• You manage marketing reporting across multiple platforms.

Final Verdict: Raw Data vs. Real Efficiency

While Google’s new export connector brings much-needed improvements, it still demands technical skills and offers limited flexibility—especially when it comes to historical data and cross-platform integration.

Dataslayer fills these gaps with an intuitive, marketer-friendly interface, robust scheduling options, and broad data source support. Whether you're building a holistic data warehouse in BigQuery or simply need a better way to manage GA4 to BigQuery data automation, Dataslayer gives you power without complexity.

Ready to simplify your GA4 data automation?

Explore how Dataslayer can supercharge your marketing data workflows in BigQuery—without the engineering overhead. Start your free trial today.