- Introduction
-
Getting Started
- Creating an Account in Hevo
- Subscribing to Hevo via AWS Marketplace
- Subscribing to Hevo via Snowflake Marketplace
- Connection Options
- Familiarizing with the UI
- Creating your First Pipeline
- Data Loss Prevention and Recovery
-
Data Ingestion
- Types of Data Synchronization
- Ingestion Modes and Query Modes for Database Sources
- Ingestion and Loading Frequency
- Data Ingestion Statuses
- Deferred Data Ingestion
- Handling of Primary Keys
- Handling of Updates
- Handling of Deletes
- Hevo-generated Metadata
- Best Practices to Avoid Reaching Source API Rate Limits
-
Edge
- Getting Started
- Data Ingestion
- Core Concepts
-
Pipelines
- Familiarizing with the Pipelines UI (Edge)
- Creating an Edge Pipeline
- Working with Edge Pipelines
- Pipeline Job History
- Object and Schema Management
- Activity Log
-
Sources
- PostgreSQL
- Oracle
- MySQL
- SQL Server
- CockroachDB
- Troubleshooting Database Sources
- Salesforce Bulk API V2
- Ordergroove
- BambooHR
- Stripe
- NetSuite SuiteAnalytics
- Shopify
- Slack
- ClickUp
- Monday.com
- Pipedrive
- Workable
- Fathom
- HubSpot
- Salesforce Marketing Cloud
- Google Analytics 4
- Naming Conventions for Source Data Entities
- Destinations
- Transformations
- Alerts
- Custom Connectors
-
Releases
- Edge Release Notes - July 21, 2026
- Edge Release Notes - July 01, 2026
- Edge Release Notes - June 22, 2026
- Edge Release Notes - June 03, 2026
- Edge Release Notes - May 25, 2026
- Edge Release Notes - April 20, 2026
- Edge Release Notes - April 09, 2026
- Edge Release Notes - March 31, 2026
- Edge Release Notes - March 26, 2026
- Edge Release Notes - March 16, 2026
- Edge Release Notes - February 18, 2026
- Edge Release Notes - February 10, 2026
- Edge Release Notes - February 03, 2026
- Edge Release Notes - January 20, 2026
- Edge Release Notes - December 08, 2025
- Edge Release Notes - December 01, 2025
- Edge Release Notes - November 05, 2025
- Edge Release Notes - October 30, 2025
- Edge Release Notes - September 22, 2025
- Edge Release Notes - August 11, 2025
- Edge Release Notes - July 09, 2025
- Edge Release Notes - November 21, 2024
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Data Loading
- Loading Data in a Database Destination
- Loading Data to a Data Warehouse
- Optimizing Data Loading for a Destination Warehouse
- Deduplicating Data in a Data Warehouse Destination
- Manually Triggering the Loading of Events
- Scheduling Data Load for a Destination
- Loading Events in Batches
- Data Loading Statuses
- Data Spike Alerts
- Name Sanitization
- Table and Column Name Compression
- Parsing Nested JSON Fields in Events
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Pipelines
- Data Flow in a Pipeline
- Familiarizing with the Pipelines UI
- Working with Pipelines
- Managing Objects in Pipelines
- Pipeline Jobs
-
Transformations
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Python Code-Based Transformations
- Supported Python Modules and Functions
-
Transformation Methods in the Event Class
- Create an Event
- Retrieve the Event Name
- Rename an Event
- Retrieve the Properties of an Event
- Modify the Properties for an Event
- Fetch the Primary Keys of an Event
- Modify the Primary Keys of an Event
- Fetch the Data Type of a Field
- Check if the Field is a String
- Check if the Field is a Number
- Check if the Field is Boolean
- Check if the Field is a Date
- Check if the Field is a Time Value
- Check if the Field is a Timestamp
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TimeUtils
- Convert Date String to Required Format
- Convert Date to Required Format
- Convert Datetime String to Required Format
- Convert Epoch Time to a Date
- Convert Epoch Time to a Datetime
- Convert Epoch to Required Format
- Convert Epoch to a Time
- Get Time Difference
- Parse Date String to Date
- Parse Date String to Datetime Format
- Parse Date String to Time
- Utils
- Examples of Python Code-based Transformations
-
Drag and Drop Transformations
- Special Keywords
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Transformation Blocks and Properties
- Add a Field
- Change Datetime Field Values
- Change Field Values
- Drop Events
- Drop Fields
- Find & Replace
- Flatten JSON
- Format Date to String
- Format Number to String
- Hash Fields
- If-Else
- Mask Fields
- Modify Text Casing
- Parse Date from String
- Parse JSON from String
- Parse Number from String
- Rename Events
- Rename Fields
- Round-off Decimal Fields
- Split Fields
- Examples of Drag and Drop Transformations
- Effect of Transformations on the Destination Table Structure
- Transformation Reference
- Transformation FAQs
-
Python Code-Based Transformations
-
Schema Mapper
- Using Schema Mapper
- Mapping Statuses
- Auto Mapping Event Types
- Manually Mapping Event Types
- Modifying Schema Mapping for Event Types
- Schema Mapper Actions
- Fixing Unmapped Fields
- Resolving Incompatible Schema Mappings
- Resizing String Columns in the Destination
- Changing the Data Type of a Destination Table Column
- Schema Mapper Compatibility Table
- Limits on the Number of Destination Columns
- File Log
- Troubleshooting Failed Events in a Pipeline
- Mismatch in Events Count in Source and Destination
- Audit Tables
- Activity Log
-
Pipeline FAQs
- Can multiple Sources connect to one Destination?
- What happens if I re-create a deleted Pipeline?
- Why is there a delay in my Pipeline?
- Can I change the Destination post-Pipeline creation?
- Why is my billable Events high with Delta Timestamp mode?
- Can I drop multiple Destination tables in a Pipeline at once?
- How does Run Now affect scheduled ingestion frequency?
- Will pausing some objects increase the ingestion speed?
- Can I see the historical load progress?
- Why is my Historical Load Progress still at 0%?
- Why is historical data not getting ingested?
- How do I set a field as a primary key?
- How do I ensure that records are loaded only once?
- Why can't I see my Pipelines after logging in?
- Events Usage
-
Sources
- Free Sources
-
Databases and File Systems
- Data Warehouses
-
Databases
- Connecting to a Local Database
- Amazon DocumentDB
- Amazon DynamoDB
- Elasticsearch
-
MongoDB
- Generic MongoDB
- MongoDB Atlas
- Support for Multiple Data Types for the _id Field
- Example - Merge Collections Feature
-
Troubleshooting MongoDB
-
Errors During Pipeline Creation
- Error 1001 - Incorrect credentials
- Error 1005 - Connection timeout
- Error 1006 - Invalid database hostname
- Error 1007 - SSH connection failed
- Error 1008 - Database unreachable
- Error 1011 - Insufficient access
- Error 1028 - Primary/Master host needed for OpLog
- Error 1029 - Version not supported for Change Streams
- SSL 1009 - SSL Connection Failure
- Troubleshooting MongoDB Change Streams Connection
- Troubleshooting MongoDB OpLog Connection
-
Errors During Pipeline Creation
- SQL Server
-
MySQL
- Amazon Aurora MySQL
- Amazon RDS MySQL
- Azure MySQL
- Generic MySQL
- Google Cloud MySQL
- MariaDB MySQL
-
Troubleshooting MySQL
-
Errors During Pipeline Creation
- Error 1003 - Connection to host failed
- Error 1006 - Connection to host failed
- Error 1007 - SSH connection failed
- Error 1011 - Access denied
- Error 1012 - Replication access denied
- Error 1017 - Connection to host failed
- Error 1026 - Failed to connect to database
- Error 1027 - Unsupported BinLog format
- Failed to determine binlog filename/position
- Schema 'xyz' is not tracked via bin logs
- Errors Post-Pipeline Creation
-
Errors During Pipeline Creation
- MySQL FAQs
- Oracle
-
PostgreSQL
- Amazon Aurora PostgreSQL
- Amazon RDS PostgreSQL
- Azure PostgreSQL
- Generic PostgreSQL
- Google Cloud PostgreSQL
- Heroku PostgreSQL
- Upgrading Pipelines with PostgreSQL Sources to Use the pgoutput Plugin
-
Troubleshooting PostgreSQL
-
Errors during Pipeline creation
- Error 1003 - Authentication failure
- Error 1006 - Connection settings errors
- Error 1011 - Access role issue for logical replication
- Error 1012 - Access role issue for logical replication
- Error 1014 - Database does not exist
- Error 1017 - Connection settings errors
- Error 1023 - No pg_hba.conf entry
- Error 1024 - Number of requested standby connections
- Errors Post-Pipeline Creation
-
Errors during Pipeline creation
-
PostgreSQL FAQs
- Can I track updates to existing records in PostgreSQL?
- How can I migrate a Pipeline created with one PostgreSQL Source variant to another variant?
- How can I prevent data loss when migrating or upgrading my PostgreSQL database?
- Why do FLOAT4 and FLOAT8 values in PostgreSQL show additional decimal places when loaded to BigQuery?
- Why is data not being ingested from PostgreSQL Source objects?
- Troubleshooting Database Sources
- Database Source FAQs
- File Storage
- Engineering Analytics
- Finance & Accounting Analytics
-
Marketing Analytics
- ActiveCampaign
- AdRoll
- Amazon Ads
- Apple Search Ads
- AppsFlyer
- CleverTap
- Criteo
- Drip
- Facebook Ads
- Facebook Page Insights
- Firebase Analytics
- Freshsales
- Google Ads
- Google Analytics 4
- Google Analytics 360
- Google Play Console
- Google Search Console
- HubSpot
- Instagram Business
- Klaviyo v2
- Lemlist
- LinkedIn Ads
- Mailchimp
- Mailshake
- Marketo
- Microsoft Ads
- Onfleet
- Outbrain
- Pardot
- Pinterest Ads
- Pipedrive
- Recharge
- Segment
- SendGrid Webhook
- SendGrid
- Salesforce Marketing Cloud
- Snapchat Ads
- SurveyMonkey
- Taboola
- TikTok Ads
- Twitter Ads
- Typeform
- YouTube Analytics
- Product Analytics
- Sales & Support Analytics
- Source FAQs
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Destinations
- Familiarizing with the Destinations UI
- Cloud Storage-Based
- Databases
-
Data Warehouses
- Amazon Redshift
- Amazon Redshift Serverless
- Azure Synapse Analytics
- Databricks
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Google BigQuery
- Clustering in BigQuery
- Partitioning in BigQuery
- Structure of Data in the Google BigQuery Data Warehouse
- Loading Data to a Google BigQuery Data Warehouse
- Near Real-time Data Loading using Streaming
- Modifying BigQuery Destinations to Use Service Account Authentication
- Troubleshooting Google BigQuery
- Google BigQuery FAQs
- Hevo Managed Google BigQuery
- Snowflake
- Troubleshooting Data Warehouse Destinations
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Destination FAQs
- Can I change the primary key in my Destination table?
- Can I change the Destination table name after creating the Pipeline?
- How can I change or delete the Destination table prefix?
- Why does my Destination have deleted Source records?
- How do I filter deleted Events from the Destination?
- Does a data load regenerate deleted Hevo metadata columns?
- How do I filter out specific fields before loading data?
- Transform
- Alerts
- Account Management
- Activate
- Glossary
-
Releases- Release 2.50.2 (July 06-13, 2026)
- Release 2.50.1 (June 29-July 06, 2026)
- 2026 Releases
-
2025 Releases
- Release 2.44 (Dec 01, 2025-Jan 12, 2026)
- Release 2.43 (Nov 03-Dec 01, 2025)
- Release 2.42 (Oct 06-Nov 03, 2025)
- Release 2.41 (Sep 08-Oct 06, 2025)
- Release 2.40 (Aug 11-Sep 08, 2025)
- Release 2.39 (Jul 07-Aug 11, 2025)
- Release 2.38 (Jun 09-Jul 07, 2025)
- Release 2.37 (May 12-Jun 09, 2025)
- Release 2.36 (Apr 14-May 12, 2025)
- Release 2.35 (Mar 17-Apr 14, 2025)
- Release 2.34 (Feb 17-Mar 17, 2025)
- Release 2.33 (Jan 20-Feb 17, 2025)
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2024 Releases
- Release 2.32 (Dec 16 2024-Jan 20, 2025)
- Release 2.31 (Nov 18-Dec 16, 2024)
- Release 2.30 (Oct 21-Nov 18, 2024)
- Release 2.29 (Sep 30-Oct 22, 2024)
- Release 2.28 (Sep 02-30, 2024)
- Release 2.27 (Aug 05-Sep 02, 2024)
- Release 2.26 (Jul 08-Aug 05, 2024)
- Release 2.25 (Jun 10-Jul 08, 2024)
- Release 2.24 (May 06-Jun 10, 2024)
- Release 2.23 (Apr 08-May 06, 2024)
- Release 2.22 (Mar 11-Apr 08, 2024)
- Release 2.21 (Feb 12-Mar 11, 2024)
- Release 2.20 (Jan 15-Feb 12, 2024)
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2023 Releases
- Release 2.19 (Dec 04, 2023-Jan 15, 2024)
- Release Version 2.18
- Release Version 2.17
- Release Version 2.16 (with breaking changes)
- Release Version 2.15 (with breaking changes)
- Release Version 2.14
- Release Version 2.13
- Release Version 2.12
- Release Version 2.11
- Release Version 2.10
- Release Version 2.09
- Release Version 2.08
- Release Version 2.07
- Release Version 2.06
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2022 Releases
- Release Version 2.05
- Release Version 2.04
- Release Version 2.03
- Release Version 2.02
- Release Version 2.01
- Release Version 2.00
- Release Version 1.99
- Release Version 1.98
- Release Version 1.97
- Release Version 1.96
- Release Version 1.95
- Release Version 1.93 & 1.94
- Release Version 1.92
- Release Version 1.91
- Release Version 1.90
- Release Version 1.89
- Release Version 1.88
- Release Version 1.87
- Release Version 1.86
- Release Version 1.84 & 1.85
- Release Version 1.83
- Release Version 1.82
- Release Version 1.81
- Release Version 1.80 (Jan-24-2022)
- Release Version 1.79 (Jan-03-2022)
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2021 Releases
- Release Version 1.78 (Dec-20-2021)
- Release Version 1.77 (Dec-06-2021)
- Release Version 1.76 (Nov-22-2021)
- Release Version 1.75 (Nov-09-2021)
- Release Version 1.74 (Oct-25-2021)
- Release Version 1.73 (Oct-04-2021)
- Release Version 1.72 (Sep-20-2021)
- Release Version 1.71 (Sep-09-2021)
- Release Version 1.70 (Aug-23-2021)
- Release Version 1.69 (Aug-09-2021)
- Release Version 1.68 (Jul-26-2021)
- Release Version 1.67 (Jul-12-2021)
- Release Version 1.66 (Jun-28-2021)
- Release Version 1.65 (Jun-14-2021)
- Release Version 1.64 (Jun-01-2021)
- Release Version 1.63 (May-19-2021)
- Release Version 1.62 (May-05-2021)
- Release Version 1.61 (Apr-20-2021)
- Release Version 1.60 (Apr-06-2021)
- Release Version 1.59 (Mar-23-2021)
- Release Version 1.58 (Mar-09-2021)
- Release Version 1.57 (Feb-22-2021)
- Release Version 1.56 (Feb-09-2021)
- Release Version 1.55 (Jan-25-2021)
- Release Version 1.54 (Jan-12-2021)
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2020 Releases
- Release Version 1.53 (Dec-22-2020)
- Release Version 1.52 (Dec-03-2020)
- Release Version 1.51 (Nov-10-2020)
- Release Version 1.50 (Oct-19-2020)
- Release Version 1.49 (Sep-28-2020)
- Release Version 1.48 (Sep-01-2020)
- Release Version 1.47 (Aug-06-2020)
- Release Version 1.46 (Jul-21-2020)
- Release Version 1.45 (Jul-02-2020)
- Release Version 1.44 (Jun-11-2020)
- Release Version 1.43 (May-15-2020)
- Release Version 1.42 (Apr-30-2020)
- Release Version 1.41 (Apr-2020)
- Release Version 1.40 (Mar-2020)
- Release Version 1.39 (Feb-2020)
- Release Version 1.38 (Jan-2020)
- Early Access New
Edge Pipeline is now available for Public Review. You can explore and evaluate its features and share your feedback.
Google Analytics 4 is Google’s web and app analytics platform that uses an event-based data model to measure customer interactions across websites and applications. It provides acquisition, engagement, monetization, and retention reports, along with machine learning-powered insights, so you can understand the complete customer journey and make data-driven marketing and product decisions.
Hevo uses the Google Analytics Data API to replicate prebuilt and custom report objects and the Google Analytics Admin API to replicate metadata objects from your Google Analytics 4 account to the Destination of your choice. To ingest data, you must authenticate your Google Analytics 4 account with Hevo using Open Authorization (OAuth).
Supported Features
| Feature Name | Supported |
|---|---|
| Capture deletes | No |
| History mode | No |
| Custom data (user-configured tables & fields) | Yes |
| Data blocking (skip objects and fields) | Yes |
| Resync (objects and Pipelines) | Yes |
| API configurable | Yes |
Prerequisites
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An active Google Analytics 4 property exists from which data is to be ingested.
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The Google account you use to authorize Hevo has at least Viewer access to the Google Analytics 4 accounts and properties you want to sync.
Configure Google Analytics 4 as a Source in your Pipeline
Perform the following steps to configure your Google Analytics 4 Source:
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Click Pipelines in the Navigation Bar.
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Click + Create Pipeline in the Pipelines List View.
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On the Select Source Type page, select Google Analytics 4.
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On the Select Destination Type page, select the type of Destination you want to use.
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On the Select Pipeline Type page, click Edge, and then click Continue.

This page appears only if the selected Destination type is supported in Edge and your Team has an existing Google Analytics 4 Pipeline with the same Destination type. Otherwise, you can proceed to create an Edge Pipeline.
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In the Configure Source screen, specify the following:

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Source Name: A unique name for your Source, not exceeding 255 characters. For example, Google Analytics 4 Source.
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In the Connect to your Google Analytics 4 account section, specify the following:
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Google Account: Click the button to authorize Hevo. In the Google sign-in window that opens, select the Google account that has access to your Google Analytics 4 properties, review the requested permissions, and click Allow.
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Account Selection: From the drop-down, select whether Hevo syncs data from all the accounts accessible to the authorized Google account, or only from specific accounts that you select.
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Historical Sync Duration: From the drop-down, select how far back Hevo fetches data on the first Pipeline run. Default: 6 Months. You cannot change this value after the Pipeline is created.
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(Optional) Rollback Window (days): Specify the number of days for which Hevo re-fetches previously ingested report data to capture updated report data. Min: 2 days. Max: 90 days. Default: 30 days.
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If you choose Sync Specific Accounts in the Account Selection field, the Properties to sync section appears. Specify the following:
- Properties to sync: From the drop-down, select the Google Analytics 4 properties whose data you want to ingest.
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(Optional) In the Custom Reports section, define one or more custom reports. Each report you define is ingested into its own table in the Destination. To add a report, specify the following:

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Report Name: A unique name for the report. This cannot be changed after the report is created.
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Report Fields: Select the dimensions and metrics for the report from tabs grouped by category, such as Traffic Source, Ecommerce, Geography, Event-Scoped Custom Dimensions, and User-Scoped Custom Dimensions. Alternatively, you can pick a report template to automatically select the fields for a pre-built report.
Note: A report can include a maximum of 9 dimensions and 10 metrics, and must include a date dimension that matches the selected Aggregation.
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Aggregation: From the drop-down, select the time interval used to group the report data. Default value: Daily. You cannot change this value after the report is created. The Report Fields you select must include a matching date dimension: Date for Daily, Year week for Weekly, Year month for Monthly, and Year for Yearly.
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(Optional) Filter Dimension: The Google Analytics 4 dimension used to filter the report data, for example, Country.
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Filter Operator: The condition used to match the selected Filter Dimension.
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Filter Type: Determines whether rows that match the filter condition are included in or excluded from the report.
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(Optional) Filter Values: The value or values to match for the selected Filter Dimension. Enter comma-separated values if the Filter Operator is Exact match, or a single value if the Filter Operator is Contains.
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Note: Changing the properties to sync removes any unsaved custom report configuration.
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Click Test & Continue to test the connection to your Google Analytics 4 Source. Once the test is successful, you can proceed to set up your Destination.
Data Replication
Hevo replicates data for all the objects selected on the Configure Objects page during Pipeline creation. By default, all supported objects and their available fields are selected. However, you can modify this selection while creating or editing the Pipeline.
Hevo ingests the following types of data from your Source objects:
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Historical Data: The first run of the Pipeline ingests historical data for the selected reports based on the historical sync duration specified when creating the Pipeline, and loads it into the Destination.
-
Incremental Data: Once the historical load is complete, new and updated records for objects are ingested as per the sync frequency.
For all prebuilt and custom reports, Hevo ingests only the incremental data using the date field in subsequent Pipeline runs. During each sync, Hevo also re-fetches data for the number of days specified in the Rollback Window (days) field to capture any revisions to previously ingested report data. This ensures that your Destination stays up to date.
If you add a new custom report to an existing Pipeline, Hevo ingests its historical data based on the historical sync duration specified when the Pipeline was created. Existing reports continue syncing only incremental data.
For all metadata objects fetched through the Google Analytics Admin API, Hevo ingests the entire data during each Pipeline run.
Before each Pipeline run, Hevo checks for any new custom dimensions or metrics in your Google Analytics 4 property. This ensures that they are available the next time you configure a custom report in Hevo.
The Google Analytics Data API enforces the following quotas per property:
-
Standard properties are limited to 200,000 core tokens per day and 40,000 core tokens per hour, with a maximum of 10 concurrent requests per property.
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Analytics 360 properties are limited to 2,000,000 core tokens per day and 400,000 core tokens per hour, with a maximum of 50 concurrent requests per property.
If this limit is exceeded, a rate limit exception occurs. To understand how Hevo handles such scenarios, read Handling Rate Limit Exceptions.
Note: You can create a Pipeline with this Source only using the Merge load mode. The Append mode is not supported for this Source.
Schema and Primary Keys
Hevo uses the following schema to upload the records to the Destination. For a detailed view of the objects, fields, and relationships, click the ERD.
Data Model
The following is the list of tables (objects) that are created at the Destination when you run the Pipeline:
Google Analytics Admin API - Metadata Objects
| Object | Description |
|---|---|
| Account | Contains details about the Google Analytics accounts accessible to the authorized Google account, including the account’s display name, region, and creation and last-updated timestamps. |
| Property | Contains details about each Google Analytics 4 property under your accounts, such as the property’s display name, industry category, currency, time zone, and service level. |
| Conversion Event | Contains the conversion events (also known as key events) configured for a property, including the event name, whether it is a custom event, and whether it can be deleted. |
| Custom Dimension | Contains the custom dimensions defined for a property, including the dimension’s display name, parameter name, and scope. |
| Custom Metric | Contains the custom metrics defined for a property, including the metric’s display name, parameter name, measurement unit, and scope. |
| Google Ads Link | Contains details about the Google Ads accounts linked to a property, including the linked customer ID, the email address of the user who created the link, and whether ad personalization is enabled. |
Google Analytics Data API - Prebuilt Reports
All prebuilt report objects are ingested using the Google Analytics Data API. Each object below corresponds to a fixed dimension/metric combination, aggregated by day and property.
Traffic Acquisition Reports
| Object | Description |
|---|---|
| Traffic Acquisition Session Campaign | Contains daily session, engagement, and revenue metrics broken down by the session’s campaign name. |
| Traffic Acquisition Session Default Channel Grouping | Contains daily session, engagement, and revenue metrics broken down by the session’s default channel grouping, such as Organic Search, Paid Search, Direct, or Referral. |
| Traffic Acquisition Session Medium | Contains daily session, engagement, and revenue metrics broken down by the session’s medium. |
| Traffic Acquisition Session Source | Contains daily session, engagement, and revenue metrics broken down by the session’s traffic source. |
| Traffic Acquisition Session Source Medium | Contains daily session, engagement, and revenue metrics broken down by the combination of session source and medium. |
| Traffic Acquisition Session Source Platform | Contains daily session, engagement, and revenue metrics broken down by the session’s source platform, such as Google Ads or manual tagging. |
User Acquisition Reports
| Object | Description |
|---|---|
| User Acquisition First User Campaign | Contains daily new-user acquisition, engagement, and revenue metrics broken down by the campaign that first acquired the user. |
| User Acquisition First User Google Ads Ad Group Name | Contains daily new-user acquisition, engagement, and revenue metrics broken down by the Google Ads ad group that first acquired the user. |
| User Acquisition First User Google Ads Network Type | Contains daily new-user acquisition, engagement, and revenue metrics broken down by the Google Ads network type that first acquired the user. |
| User Acquisition First User Medium | Contains daily new-user acquisition, engagement, and revenue metrics broken down by the medium that first acquired the user. |
| User Acquisition First User Source | Contains daily new-user acquisition, engagement, and revenue metrics broken down by the traffic source that first acquired the user. |
| User Acquisition First User Source Medium | Contains daily new-user acquisition, engagement, and revenue metrics broken down by the combination of source and medium that first acquired the user. |
| User Acquisition First User Source Platform | Contains daily new-user acquisition, engagement, and revenue metrics broken down by the source platform that first acquired the user. |
Demographic Reports
| Object | Description |
|---|---|
| Demographic Age | Contains daily user, engagement, and revenue metrics broken down by the user’s age bracket. |
| Demographic City | Contains daily user, engagement, and revenue metrics broken down by the user’s city. |
| Demographic Country | Contains daily user, engagement, and revenue metrics broken down by the user’s country. |
| Demographic Gender | Contains daily user, engagement, and revenue metrics broken down by the user’s gender. |
| Demographic Interests | Contains daily user, engagement, and revenue metrics broken down by the user’s affinity or in-market interest category. |
| Demographic Language | Contains daily user, engagement, and revenue metrics broken down by the user’s browser or device language. |
| Demographic Region | Contains daily user, engagement, and revenue metrics broken down by the user’s region. |
Technology & Device Reports
| Object | Description |
|---|---|
| Tech App Version | Contains daily user, engagement, and revenue metrics broken down by app version. |
| Tech Browser | Contains daily user, engagement, and revenue metrics broken down by browser. |
| Tech Device Category | Contains daily user, engagement, and revenue metrics broken down by device category, such as desktop, mobile, or tablet. |
| Tech Device Model | Contains daily user, engagement, and revenue metrics broken down by device model. |
| Tech Operating System | Contains daily user, engagement, and revenue metrics broken down by operating system. |
| Tech Os Version | Contains daily user, engagement, and revenue metrics broken down by operating system version. |
| Tech Os With Version | Contains daily user, engagement, and revenue metrics broken down by operating system and version. |
| Tech Platform | Contains daily user, engagement, and revenue metrics broken down by platform, such as Web, iOS, or Android. |
| Tech Platform Device Category | Contains daily user, engagement, and revenue metrics broken down by the combination of platform and device category. |
| Tech Screen Resolution | Contains daily user, engagement, and revenue metrics broken down by screen resolution. |
E-commerce Reports
| Object | Description |
|---|---|
| Ecommerce Purchases Item Brand | Contains daily ecommerce purchase funnel metrics, including items viewed, added to cart, purchased, item revenue, and cart-to-view and purchase-to-view rates, broken down by item brand. |
| Ecommerce Purchases Item Category | Contains daily ecommerce purchase funnel metrics broken down by item category. |
| Ecommerce Purchases Item Category 2 | Contains daily ecommerce purchase funnel metrics broken down by the item’s second category. |
| Ecommerce Purchases Item Category 3 | Contains daily ecommerce purchase funnel metrics broken down by the item’s third category. |
| Ecommerce Purchases Item Category 4 | Contains daily ecommerce purchase funnel metrics broken down by the item’s fourth category. |
| Ecommerce Purchases Item Category 5 | Contains daily ecommerce purchase funnel metrics broken down by the item’s fifth category. |
| Ecommerce Purchases Item Category (Combined) | Contains daily ecommerce purchase funnel metrics broken down by all five item category levels together. |
| Ecommerce Purchases Item Id | Contains daily ecommerce purchase funnel metrics broken down by item ID. |
| Ecommerce Purchases Item Name | Contains daily ecommerce purchase funnel metrics broken down by item name. |
Publisher Ads Reports
| Object | Description |
|---|---|
| Publisher Ads Ad Format | Contains daily publisher ad impressions, exposure, clicks, and revenue broken down by ad format. |
| Publisher Ads Ad Source | Contains daily publisher ad impressions, exposure, clicks, and revenue broken down by ad source. |
| Publisher Ads Ad Unit | Contains daily publisher ad impressions, exposure, clicks, and revenue broken down by ad unit. |
| Publisher Ads Page Path | Contains daily publisher ad impressions, exposure, clicks, and revenue broken down by page path. |
Page & Screen Reports
| Object | Description |
|---|---|
| Content Group | Contains daily page views, users, events, and revenue metrics broken down by content group. |
| Pages Path | Contains daily page views, users, events, and revenue metrics broken down by page path. |
| Pages Title And Screen Class | Contains daily page views, users, events, and revenue metrics broken down by the unified screen class, which consists of the page title for web or the screen class for apps. |
| Pages Title And Screen Name | Contains daily page views, users, events, and revenue metrics broken down by the unified screen name, which consists of the page title for web or the screen name for apps. |
Events, Conversions & Audience Reports
| Object | Description |
|---|---|
| Audiences | Contains daily user, engagement, session, and revenue metrics broken down by the Google Analytics 4 audience a user belongs to. |
| Conversions | Contains daily conversion (key event) counts, user, and revenue metrics broken down by event name. |
| Events | Contains daily event counts, user, and revenue metrics broken down by event name. |
In addition to the prebuilt reports listed above, you can define Custom Reports in the Source configuration. Each custom report you create is ingested into its own table, named after the report, containing the dimensions and metrics you select.
Additional Information
Read the detailed Hevo documentation for the following related topics:
Source Considerations
-
Some dimensions, such as demographic dimensions, may use data sampling or thresholding in Google Analytics 4 to protect user privacy. As a result, the data ingested by Hevo may differ slightly from the values shown in the Google Analytics 4 interface.
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Google Analytics 4 supports only certain combinations of dimensions and metrics in a report. If a Custom Report contains an unsupported combination, Google Analytics 4 rejects the report when you save it. You can use the GA4 Dimensions and Metrics Explorer to check the compatibility of the selected dimensions and metrics.
-
If a dimension value is unavailable for a row, Google Analytics 4 returns (not set). Hevo replicates this as an empty value in the Destination.
Limitations
- You can define a maximum of 50 custom reports per Pipeline.
Revision History
Refer to the following table for the list of key updates made to this page:
| Date | Release | Description of Change |
|---|---|---|
| Jul-21-2026 | NA | New document. |