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Which web analytics tools provide a raw event data export to BigQuery?

In the intricate domain of web analytics, the distinction between raw and aggregated data export becomes crucial for businesses and analysts seeking in-depth insights.

Whether you are considering a shift from Google Analytics 4 (GA4), seeking an alternative that offers seamless integration with BigQuery, or setting up your first web analytics tool with a priority on owning and storing raw data, this article delves into an array of web analytics tools, focusing on their ability to export raw data to BigQuery.

Raw versus aggregated data export

We define 'raw data export' as the exportation of data in its most granular form - ideally, individual rows per event or hit, or at the very least, individual sessions per user. This level of detail provides the utmost flexibility and depth for analysis, vastly different from aggregated data export, which only offers summarized information.

While almost all web analytics tools offer some form of aggregated data export, either directly or through third-party tools, the real game-changer is the capacity to handle raw data in a programmatic way and load it in a data warehouse for further use.

This capability enables users to dive deeper into user interactions, offering a microscopic view of online behavior and patterns. Our exploration includes a comparative analysis of various tools in terms of their raw data export functionalities, especially their integration with BigQuery.

Web analytics tools covered in this overview

  • Google Analytics 4 (free version & 360)
  • Adobe Analytics
  • Piwik PRO (core & enterprise)
  • Matomo (on-premise & cloud)
  • Simple Analytics
  • Mixpanel
  • Kissmetrics
  • Plausible
  • Fathom
If you don't see the complete table, scroll to the right for more info about limits, pricing and links to documentation.
Web analytics tool Raw data export Raw data export type Daily export Hourly export Streaming export Event schema Session schema Limits / remarks Tool pricing (based on 1M events per month and raw data export included, excluding BigQuery storage and query costs) More info
Google Analytics 4 ✅ Automatic export to BigQuery ✅ ❌ ✅ ✅ ❌ Daily export: 1M events (streaming export: unlimited) Free
Google Analytics 4 360 ✅ Automatic export to BigQuery ✅ ❌ ✅ ✅ ❌ Daily export: Billions of events (streaming export: unlimited) Starting at ~ $40,000 per year*
Adobe Analytics ✅ Data feed to Google Cloud Storage ✅ ✅ ❌ ✅ ❌ Requires SFTP server and loading script Starting at ~ $50,000 per year*
Piwik PRO core ✅ API - - - - - API limits apply Starting at ~ â‚Ŧ3,900 per year**
Piwik PRO enterprise ✅ Automatic export to BigQuery ✅ ✅ ❌ (coming soon) ✅ ✅ Requires one time set-up by support team. Starting at ~ â‚Ŧ10,995 per year + additional pricing for data export starting at â‚Ŧ3,099 per year**
Matomo on-premise ✅ API or read-access MySQL database - - - - - API limits apply Free (on-premise costs not included)
Matomo cloud ✅ API - - - - - API limits apply Starting at ~ â‚Ŧ1,908 per year**
Simple Analytics ✅ API or CloudQuery CLI/Cloud - - - - - API limits apply. CloudQuery requires configuration. Starting at ~ â‚Ŧ588 per year** + optional CloudQuery Cloud pricing
Mixpanel ✅ Data pipeline to Google Cloud Storage ✅ ✅ ❌ ✅ ❌ Requires loading raw JSON-files from Cloud Storage or using preconfigured schematized events Starting at ~ $1,200 per year + $240 per year data pipeline add-on**
Kissmetrics ✅ Data feed to Amazon S3 ✅ ❌ ❌ ✅ ❌ Requires configuring the Amazon S3 Data Transfer to BigQuery Starting at ~ â‚Ŧ5,988 per year** + additional pricing for data export
Plausible ❌
Fathom ❌
* Unknown, guesstimation based on dirty rumours
** Based on pricing vendor website and/or confirmed with vendor (Jan 2024)

In our overview of web analytics tools, we include pricing information, sometimes regarded as industry-sensitive data, to foster transparency and empower our readers with comprehensive knowledge for making informed decisions. By demystifying pricing, we advocate for market transparency, ensuring that our readers are equipped with all necessary details to choose a web analytics tool that aligns with both their functional needs and financial constraints.

Now it's your turn!

I hope you've enjoyed this article. Drop a line in the comments if you have any questions, feedback or suggestions related to this article.