TL;DR Short answer: GA4 has a free export to BigQuery that sends every raw event, unsampled, and for many teams that is the right starting point. Google Analytics ETL tools matter when BigQuery is not your warehouse, when you want GA4 joined to ad, CRM and revenue data in the same pipeline, or when you need history from before the export was switched on. Ten options:
Airbyte GA4 BigQuery export Fivetran Supermetrics Funnel.io Stitch Data Hevo Data Boomi Data Integration Meltano Apache Airflow One GA4 constraint: the BigQuery export starts on the day you link it, with no backfill, and the GA4 Data API that ETL tools use returns aggregated reports subject to token quotas, thresholding and an (other) row on high-cardinality dimensions. Raw events only come from the export, so switch it on now even if you also use a tool.Google Analytics ETL tools move GA4 data into a warehouse where it can be joined to everything else. Google Analytics 4 is now the only version: Universal Analytics stopped processing data in July 2023, and its data and API access ended in July 2024, so any tool or guide still built around Universal Analytics views and goals is out of date.
Why export Google Analytics data? GA4 reports well on its own data and runs out of road the moment you want to join it to anything else: revenue from your payment processor, cost from your ad platforms, or retention from your product database. Exporting also gets around GA4's own limits. Explorations sample large datasets, event-level data in explorations is retained for only two or 14 months depending on your settings, and the interface hides detail behind thresholds and (other) rows.
How do the Google Analytics ETL tools compare? Tool What you get Destinations Built for Pricing basis Airbyte Data API reports, including custom reports Any Data engineers Free self-hosted; Cloud volume-based; Pro and Flex capacity-based GA4 BigQuery export Raw, unsampled events BigQuery only Anyone on BigQuery Free; BigQuery storage and queries Fivetran Data API reports Any Data engineers Monthly active rows Supermetrics Interface dimensions and metrics Warehouses, Sheets, Looker Studio Marketing teams Plan by sources and destinations Funnel.io Reports normalised with ad data Warehouses and BI tools Marketing teams Plan by data volume Stitch Data Data API reports Major warehouses Teams with simple needs Row volume tiers Hevo Data Data API reports Major warehouses Teams without engineers Events Boomi Data Integration Data API reports Major warehouses Analytics teams Credits Meltano Data API reports via a Singer tap Any Singer target Engineers who want code Free, open source Apache Airflow Whatever you code Whatever you code Engineers orchestrating jobs Free, you run it
Which Google Analytics ETL tools should you consider? Every tool below has a GA4 connector except Airflow, which runs code you write. They split into data platforms and marketing tools, with Google's own export alongside.
1. Airbyte Airbyte is an open-source data integration platform with 700+ connectors and a community of 25,000+ data engineers. Its Google Analytics (GA4) source authenticates with Google OAuth or a service account, syncs pre-built reports and custom reports you define from GA4 dimensions and metrics, and runs incrementally by date. It loads into any Airbyte destination, so GA4 can sit next to your ad and revenue data in Snowflake or Databricks as easily as BigQuery.
What's unique about Airbyte? Connectors are open source and editable, and the Connector Development Kit and no-code Connector Builder cover anything without a pre-built connector. GA4 is rarely the only marketing source, and Airbyte moves the rest through the same pipeline. It runs as self-hosted open source, on Airbyte Cloud, or as Enterprise Flex.
2. GA4 BigQuery export GA4's BigQuery export is Google's own route and free for every property. Linked from the GA4 admin, it writes every raw event, unsampled, to a daily events table in BigQuery, with an optional streaming export for near real-time data. Standard properties are capped at 1 million events a day on the daily export, the export starts on the day you link it with no backfill, and it only writes to BigQuery. Streaming export has no event cap but adds BigQuery streaming charges.
3. Fivetran Fivetran is a closed-source, managed ELT service with 700+ connectors, including GA4. Connectors are maintained for you and schema changes are applied automatically. It bills on monthly active rows, and GA4 report tables write a fresh set of rows for each day and dimension combination, so cost grows with the number of reports you sync.
Here is a closer look at Airbyte vs Fivetran .
4. Supermetrics Supermetrics is a marketing data pipeline platform, and GA4 is one of its core sources. It exposes the dimensions and metrics you already know from the interface and loads into BigQuery, Snowflake and Redshift as well as Google Sheets and Looker Studio. The reason to pick it is that the same subscription covers Google Ads, Meta and other ad platforms, so marketing teams can blend channels without a data engineer.
5. Funnel.io Funnel is a marketing data hub with a native GA4 integration. It downloads and stores source data in its own environment, normalises naming and currencies across platforms, and exports to warehouses or BI tools, so GA4 arrives in the same shape as your ad data. That suits multi-channel marketing teams, with the trade-off that your data sits with a third party in between.
6. Stitch Data Stitch is a cloud extract-and-load platform with 140+ connectors, including GA4, originally built on the Singer specification. It has no user-defined transformations and suits straightforward loading. Qlik acquired Talend, and Stitch with it, in 2023, and now publishes a migration path from Stitch to Qlik Talend Cloud, which is worth weighing before committing.
Here is a closer look at Airbyte vs Stitch .
7. Hevo Data Hevo Data is a no-code cloud ELT platform with 150+ connectors, including GA4, and built-in transformation applied before data reaches the destination. It is cloud-only and billed on events, which suits teams without engineering capacity who do not need self-hosting.
8. Boomi Data Integration (formerly Rivery) Boomi acquired Rivery in December 2024 and now sells it as Boomi Data Integration. It has a pre-built GA4 connector and bundles transformation, orchestration and reverse ETL in one cloud platform with 150+ connectors. Pricing is in credits that vary by connector, which can make cost hard to model.
9. Meltano Meltano is an open-source, CLI-first platform spun out of GitLab that manages Singer taps and targets as a version-controlled project. It reaches GA4 through a community Singer tap. Maintenance depends on that tap's maintainers, since the wider Singer community is now largely inactive, so expect to patch it yourself when Google changes the API.
10. Apache Airflow Apache Airflow is an open-source orchestrator, not an ETL tool. You can schedule Python code that calls the GA4 Data API, but you write the authentication, quota handling and incremental logic yourself. Its common role here is scheduling dbt models on top of the GA4 BigQuery export, or running a connector-based tool such as Airbyte alongside other pipelines.
Here is a closer look at Airbyte vs Airflow .
Is the free GA4 BigQuery export enough? For many teams on BigQuery, yes. It gives you every raw event, unsampled, at no cost beyond BigQuery storage and queries, which is more complete than anything a tool can pull through the Data API. It falls short in four situations:
Your warehouse is not BigQuery. The export only writes to BigQuery, so Snowflake, Databricks or Redshift users need a tool, or a second hop from BigQuery.You need history from before the link. The export has no backfill; the Data API can return earlier aggregated reports.Your property exceeds 1 million events a day. Standard properties beyond that need streaming export, which adds cost, or GA4 360.You want report-shaped data. Raw events need SQL to rebuild sessions and attribution; Data API reports arrive pre-aggregated, matching what marketers see in GA4.Many teams use both: the export for raw events, and a tool for report-level data and for getting GA4 into a non-BigQuery warehouse alongside other sources.
The GA4 Data API, which every connector-based tool here uses, returns reports built from dimensions such as date, page, source, medium, campaign, country and device, and metrics such as active users, sessions, engagement, key events and revenue, including custom dimensions and metrics you define in GA4. A real-time report covers the last 30 minutes.
It does not return raw events, and requests draw on token-based quotas per property per hour and per day, so a large backfill across many reports can exhaust them. Results may also be thresholded when Google signals are enabled, and high-cardinality dimensions can collapse into an (other) row. Use the BigQuery export when you need event-level detail.
How do you start syncing Google Analytics data with Airbyte? Step 1: Set up Google Analytics as a source In Airbyte, open Sources, choose New source and select Google Analytics 4. Authenticate with Google OAuth, or with a service account added as a Viewer on the GA4 property. Enter the numeric property ID from GA4's admin settings and a start date, and add any custom reports you need by listing their dimensions and metrics. Run the connection test.
Step 2: Set up a destination Choose where the data lands: a cloud warehouse such as Snowflake, BigQuery or Redshift, a data lake, a database or cloud storage.
Step 3: Configure the connection Select the reports you need, use incremental sync, and set a daily schedule. GA4 data settles over a day or two as late events arrive, so a short lookback window keeps recent days accurate.
The process is the same in Airbyte Open Source, which you can deploy yourself , and in Airbyte Cloud, which you can try free for 14 days .
Which Google Analytics ETL tool should you choose? Switch on the GA4 BigQuery export first: it is free, it is the only source of raw events, and it cannot backfill. Then choose by who owns the pipeline. If data engineering does and GA4 is one of many sources, Airbyte brings it into any warehouse alongside the rest, self-hosted or in Cloud, and Fivetran does the same with no upkeep if row-based pricing works for you. If marketing owns it and the goal is blending channels, Supermetrics or Funnel.io fit better. Hevo, Boomi and Stitch suit simpler no-code needs.
For tools that cover more than Google Analytics, see our guide to the top data integration tools .
Frequently Asked Questions (FAQs) 1. Is the GA4 BigQuery export free? Yes, for every GA4 property. You pay only standard BigQuery charges for storage and queries, plus streaming charges if you enable streaming export. Standard properties are limited to 1 million events a day on the daily export.
2. Can you backfill the GA4 BigQuery export? No. The export starts on the day you link GA4 to BigQuery. For earlier periods, use the GA4 Data API through an ETL tool, which returns aggregated reports rather than raw events.
3. Why don't GA4 API numbers match the interface? Common causes are thresholding when Google signals are enabled, high-cardinality dimensions collapsing into an (other) row, sampling in explorations, and data that is still settling for the last day or two. Comparing like-for-like reports over settled dates usually closes the gap.
4. Can you still export Universal Analytics data? No. Universal Analytics stopped processing data in July 2023, and access to its data and API ended in July 2024. Any UA history you did not export before then is no longer available.
5. How do you get GA4 data into Snowflake? Use an ETL tool with a GA4 source and a Snowflake destination, such as Airbyte or Fivetran, which pulls reports through the Data API. For raw events, export GA4 to BigQuery first, then move those tables to Snowflake with a BigQuery source.
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