- 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
- Upgrading Pipeline from Standard to Edge
-
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
- Data Ingestion
- Core Concepts
-
Pipelines
- Familiarizing with the Pipelines UI
- Creating an Edge Pipeline
- Working with Edge Pipelines
- Pipeline Job History
- Pipeline Overview
- Needs Attention
- Object and Schema Management
- Activity Log
-
Sources
- Connect AI
- PostgreSQL
- Oracle
- MySQL
- SQL Server
- Troubleshooting Database Sources
- CockroachDB
- MongoDB
- SharePoint
- Salesforce Bulk API V2
- Ordergroove
- BambooHR
- Stripe
- NetSuite SuiteAnalytics
- Shopify
- Slack
- ClickUp
- Monday.com
- Pipedrive
- Workable
- Fathom
- HubSpot
- Salesforce Marketing Cloud
- Google Analytics 4
- Google Ads
- Facebook Ads
- Microsoft Ads
- LinkedIn Ads
- Xero
- Instagram Business
- Amazon Selling Partner
- TikTok Ads
- StackAdapt
- Amazon Ads
- Pinterest Organic
- Zendesk Support
- Snapchat Ads
- TikTok Organic
- Google Search Console
- Klaviyo v2
- Braintree Payments
- Facebook Pages
- Tempo
- PayPal
- Auth0
- Pinterest Ads
- Apple Search Ads
- Permit.io
- Amplitude Analytics
- Customer.io
- Paddle
- Jira Cloud
- Fullstory
- GitHub
- WorkOS
- ActiveCampaign
- Campaign Monitor
- Infobip
- Mailgun Send
- Metaplane
- Notion
- Recharge
- sevdesk
- Statuspage
- Teamwork.com
- Workday RaaS
- Yotpo
- TikTok Shop Partner Center
- Linear
- Microsoft Dynamics 365 Business Central
- Checkout.com
- Pylon
- Increase
- Microsoft Teams
- Rollbar
- Toggl Track
- QuickBooks Online
- Zoho Desk
- Livestorm
- Attentive
- SendGrid
- Bitly
- Shortcut
- Buzzsprout
- Persona
- Mailjet
- Open Exchange Rates
- PagerDuty
- CircleCI
- SonarQube
- Chargebee
- Bing Webmaster Tools
- Rundeck
- Cal.com
- Mixpanel
- Matomo
- Walmart Marketplace
- Xray
- Reddit Ads
- Zoho Recruit
- Freshchat
- Zoho Books
- Outreach
- Airtable
- Attio
- Okta
- Naming Conventions for Source Data Entities
- Destinations
- Transformations
- Alerts
- Activate
- Custom Connectors
-
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
-
Pipelines
- Data Flow in a Pipeline
- Familiarizing with the Pipelines UI
- Working with Pipelines
- Managing Objects in Pipelines
- Pipeline Jobs
-
Transformations
-
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
-
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
-
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
-
Destinations
- Familiarizing with the Destinations UI
- Cloud Storage-Based
- Databases
-
Data Warehouses
- Amazon Redshift
- Amazon Redshift Serverless
- Azure Synapse Analytics
- Databricks
-
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
-
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-
2026 Releases
- Release 2.53 (August 24 – September 21, 2026)
- Release 2.52 (July 27 – August 24, 2026)
- Release 2.51 (Jun 29 – July 27 , 2026)
- Release 2.50 (Jun 01–29, 2026)
- Release 2.49 (May 04-Jun 01, 2026)
- Release 2.48 (Apr 06-May 04, 2026)
- Release 2.47 (Mar 09-Apr 06, 2026)
- Release 2.46 (Feb 09-Mar 09, 2026)
- Release 2.45 (Jan 12-Feb 09, 2026)
-
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)
-
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)
-
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
-
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)
-
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)
-
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)
-
2026 Releases
- Early Access New
Matomo (Edge)
Edge Pipeline is now available for Public Review. You can explore and evaluate its features and share your feedback.
Matomo is a privacy-focused web analytics platform. It tracks the visits, page views, and events on your websites and creates reports from them, while you retain ownership of your analytics data.
Hevo uses the Matomo Reporting API to replicate the site, event, visit time, visitor interest, and insight reports of your Matomo Cloud account to the Destination of your choice. To ingest data, you must provide Hevo with the subdomain of your Matomo Cloud account and an authentication token (Auth Token) created in your Matomo account.
Supported Features
| Feature Name | Supported |
|---|---|
| Capture deletes | Yes (for the Multi Site object) |
| History mode | No |
| Custom data (user-configured tables & fields) | No |
| Data blocking (skip objects and fields) | Yes |
| Resync (objects and Pipelines) | Yes |
| API configurable | Yes |
Prerequisites
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An active Matomo Cloud account exists from which data is to be ingested. Self-hosted Matomo (Matomo On-Premise) is not supported.
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The Matomo user who creates the Auth Token has at least View access to the sites whose data you want to ingest.
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An Auth Token with View access is available.
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The subdomain of your Matomo Cloud account is available. For example, if you access Matomo at https://acme.matomo.cloud, your subdomain is acme.
Obtain the Auth Token
Hevo connects to your Matomo Cloud account using an Auth Token. The token has the same access to sites as the Matomo user who creates it, up to the token access level that you select. Hevo ingests data only for the sites that the token can access. Hence, create the token as a user who has access to all the sites whose data you want to ingest.
Perform the following steps to create an Auth Token:
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Log in to your Matomo Cloud account.
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In the top-right corner of the page, click the Administration (gear) icon.

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In the left navigation pane, under Personal, click Security.

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Scroll down to the Auth tokens section, and click CREATE NEW TOKEN. If prompted, enter your Matomo password and click CONFIRM.

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On the Auth tokens page, do the following:
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In the Description field, enter a name for the token. For example, Hevo.
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From the Token access level drop-down, select View. This access level is sufficient for Hevo to read your reports.
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(Optional) In the Expire date section, set the Token expire date. By default, the token expires 180 days after it is created. To create a token that does not expire, clear the Enable token expiration check box.
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Click CREATE NEW TOKEN.

-
-
Click the copy icon to copy the token, and save it securely like any other password.
Note: Matomo displays the token only once. After you leave this page, you cannot view the token again.

Read What is the token_auth and where can I find this token to use in the API calls? for more information.
If the Auth Token expires or is deleted, or the Matomo user who created it is removed, Hevo cannot connect to your account, and the Pipeline fails. To resume data ingestion, modify the Source configuration in the Pipeline with a valid Auth Token.
Configure Matomo as a Source in your Pipeline
Perform the following steps to configure your Matomo 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 Matomo.
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On the Select Destination Type page, select the type of Destination you want to use.
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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, Matomo Source.
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In the Connect to Matomo section, specify the following:
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Subdomain: The part before .matomo.cloud in the URL of your Matomo Cloud account. For example, acme for https://acme.matomo.cloud. If you enter the full URL, Hevo uses only the subdomain from it. You cannot change this value after the Pipeline is created.
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Auth Token: The Auth Token that you created in your Matomo account. You can change this value after the Pipeline is created.
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-
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Click Test & Continue to test the connection to your Matomo Source. Once the test is successful, you can proceed to set up your Destination.
When you click this button, Hevo checks that it can connect to the Matomo Reporting API of your account with the specified subdomain and Auth Token.
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 the reports of the last 365 days for each site in your Matomo account and loads them into the Destination.
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Incremental Data: Once the historical load is complete, new and updated report data is ingested as per the sync frequency.
Hevo ingests incremental data for the objects as follows:
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Event Action, Event Category, Event Name, and Visitor Interest: These objects contain daily reports. In each run, Hevo ingests the reports from the most recent date ingested for each site up to the current date. As a result, the report of the current day is updated in each run until the day ends.
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Insight Overview and Visit Time: These objects contain reports for a date range, which is stored in the date field in the format start date,end date. The first run ingests the report for the last 365 days. Each subsequent run ingests the report for the range from the end date of the previous run to the current date. The records of earlier date ranges are retained in the Destination. Each record is the report for its own date range, so filter on a single date value when you query these objects, instead of adding up the records of different date ranges.
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Multi Site: Hevo ingests the entire data of this object in each run. The visit, action, page view, and revenue values in this object are for the last 365 days.
Note: You can create a Pipeline with this Source only using the Merge load mode. The Append mode is not supported for this Source.
Currently, Matomo Cloud enforces a rate limit of 350 requests per minute or 2,000 requests every ten minutes, whichever is reached first, for each IP address. If this limit is exceeded, a rate limit exception occurs. To understand how Hevo handles such scenarios, read Handling Rate Limit Exceptions.
Schema and Primary Keys
Hevo uses the following schema to upload the records in 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:
| Object | Description |
|---|---|
| Event Action | Contains the daily event statistics of each site grouped by event action, such as the number of events, the number of visits with events, and the minimum, maximum, average, and total event values. Each record is linked to the Multi Site object through the id_site field. |
| Event Category | Contains the daily event statistics of each site grouped by event category, such as the number of events, the number of visits with events, and the minimum, maximum, average, and total event values. Each record is linked to the Multi Site object through the id_site field. |
| Event Name | Contains the daily event statistics of each site grouped by event name, such as the number of events, the number of visits with events, and the maximum, average, and total event values. Each record is linked to the Multi Site object through the id_site field. |
| Insight Overview | Contains the insights of each site for a date range, which compare the visits in the range with the previous period, such as the new and previous values, the difference, the growth percentage, and whether an item is new, has disappeared, or is a mover. Each record is linked to the Multi Site object through the multi_site_id field. |
| Multi Site | Contains an overview of each site in your Matomo account that has data in the last 365 days, such as the site name, main URL, and currency, and the number of visits, actions, and page views, and the revenue in this period, along with their values for the previous period and the change between the periods. |
| Visit Time | Contains the visit statistics of each site for a date range grouped by day of the week, such as the number of visits, actions, unique visitors, users, converted visits, and bounces, and the total visit length. Each record is linked to the Multi Site object through the multi_site_id field. |
| Visitor Interest | Contains the daily number of visits of each site grouped by the number of pages viewed in a visit. Each record is linked to the Multi Site object through the multi_site_id field. |
Additional Information
Read the detailed Hevo documentation for the following related topics:
Handling of Deletes
Hevo captures deletes only for the Multi Site object. As Hevo ingests the entire data of this object in each run, it compares the data fetched from the Source with the data present in the Destination table. If a site exists in the Destination but is no longer returned by the Source, Hevo marks the record as deleted by setting the value of the metadata column __hevo__marked_deleted to True. A site is not returned by the Source if it is deleted from your Matomo account, if the Auth Token can no longer access it, or if it has no data in the last 365 days.
The following objects do not support capturing deletes:
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Event Action
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Event Category
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Event Name
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Insight Overview
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Visit Time
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Visitor Interest
Source Considerations
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Hevo ingests data only for the sites that have data in the last 365 days. A site without any visits in this period is not added to the Multi Site object, and no reports are ingested for it. If a site that Hevo ingested earlier has no visits in the last 365 days, Hevo marks it as deleted in the Multi Site object.
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Matomo includes tracked visits and events in its reports only after it processes them. Hence, recent visits are ingested in the run after Matomo has processed them.
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By default, a Matomo Auth Token expires 180 days after it is created. Once the token expires, the Pipeline fails. To avoid this, create a token without an expiry date, or update the Auth Token in the Pipeline before it expires.
Limitations
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Hevo supports only Matomo Cloud accounts. You cannot ingest data from a self-hosted Matomo (Matomo On-Premise) instance.
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Hevo ingests the reports of only the last 365 days during the first run of the Pipeline. Older reports are not ingested.
Revision History
Refer to the following table for the list of key updates made to this page:
| Date | Release | Description of Change |
|---|---|---|
| Nov-06-2026 | 2.54 | New document. |