- 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
- CockroachDB
- MongoDB
- 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
- 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
- GitHub
- WorkOS
- ActiveCampaign
- Campaign Monitor
- Mailgun Send
- Metaplane
- Recharge
- sevdesk
- Statuspage
- Teamwork.com
- Workday RaaS
- Yotpo
- TikTok Shop Partner Center
- Naming Conventions for Source Data Entities
- Destinations
- Transformations
- Alerts
- Activate
- Custom Connectors
-
Releases
- Edge Release Notes - October 2026
- Edge Release Notes - September 2026
- Edge Release Notes - August 2026
- Edge Release Notes - July 2026
- Edge Release Notes - June 2026
- Edge Release Notes - May 2026
- Edge Release Notes - April 2026
- Edge Release Notes - March 2026
- Edge Release Notes - February 2026
- Edge Release Notes - January 2026
- Edge Release Notes - December 2025
- Edge Release Notes - November 2025
- Edge Release Notes - October 2025
- Edge Release Notes - September 2025
- Edge Release Notes - August 2025
- Edge Release Notes - July 2025
- Edge Release Notes - November 2024
-
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
-
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
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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)
-
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)
- Early Access New
Priority-First Sync (Edge)
When you create a Pipeline, Hevo first ingests the historical data in your Source, and then ingests new and updated data in each subsequent run. For Sources with a large volume of historical data, the historical sync can take several hours or even days, and no data is available in your Destination until it completes.
Priority-first sync reduces this wait by loading your most recent data first. In the first run of the Pipeline, Hevo ingests the data from a recent period, such as the last 30 days, and loads it into your Destination before the older data. You can start using your recent data while Hevo continues to load the older data.
Note: Currently, Stripe is the only Source that supports priority-first sync. It is enabled by default, and you do not need to configure anything to use it. Priority-first sync applies whenever Hevo ingests the historical data of a Pipeline, including when you resync it.
Understanding Priority-First Sync
With priority-first sync, Hevo splits the historical load into two parts, based on a period called the priority fetch period:
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Recent data: The data created within the priority fetch period. Hevo fetches this data first. For Pipelines created with Stripe as the Source, the priority fetch period is 30 days.
-
Older data: All the data older than the priority fetch period. Hevo fetches this data in one or more Pipeline runs.
Priority-first sync applies only to a specific set of objects, called the priority objects. For all the other objects in your Pipeline, Hevo ingests the entire data along with the older data.
In Pipelines created with Stripe as the Source, the following objects and their child objects are synced on a priority-first basis:
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Account
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Application Fee
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Authorization
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Balance Transaction
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Cardholder
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Charge
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Coupon
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Customer
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Dispute
-
File
-
File Link
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Invoice
-
Invoice Item
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Issuing Card
-
Issuing Dispute
-
Issuing Transaction
-
Payment Intent
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Payout
-
Price
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Product
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Promotion Code
-
Refund
-
Review
-
Setup Intent
-
Shipping Rate
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Subscription History
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Subscription Schedule
-
Tax Rate
-
Topup
-
Transfer
Refer to the following sections for information about the jobs that Hevo runs in each Pipeline run:
-
First Run of the Pipeline: Describes the two historical jobs that Hevo starts when the Pipeline runs for the first time, and the order in which their data is loaded.
-
Subsequent Runs of the Pipeline: Describes the jobs that Hevo runs in each run after the first one, until all the older data is ingested.
First Run of the Pipeline
In the first run, Hevo starts two historical jobs at the same time:
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Priority sync: Ingests the recent data for the priority objects and their child objects.
-
Backward sync: Ingests the older data for the priority objects, and all the data for the remaining objects in your Pipeline.
Both jobs ingest data at the same time, but Hevo loads the data of the priority sync into your Destination first. The backward sync loads its data only after the priority sync completes.
The backward sync runs for a limited time, called the backward sync duration, which is 6 hours for Pipelines created with Stripe as the Source. If the job cannot ingest all the older data within this time, it stops, and the remaining data is ingested in the subsequent runs. The job may run slightly longer than this duration to complete the data it is processing.
During the first run, Hevo does not run incremental jobs. Incremental data is ingested from the next run onwards.
Note: If the backward sync fails during the first run, Hevo marks both jobs as failed. However, the data that the priority sync has already loaded into your Destination is retained.
Subsequent Runs of the Pipeline
In each subsequent run, Hevo first runs an incremental job to ingest the new and updated data in your Source. If some older data is still pending, Hevo then runs a backward sync that continues from where the previous one stopped. Each backward sync runs for up to the backward sync duration.
Hevo repeats this in every run until all the older data is ingested. After that, the Pipeline runs only incremental jobs.
Note: As the incremental job runs before the backward sync in each run, your Destination receives new and updated data on schedule, even while the older data is still being loaded.
The following table shows an example of how data is loaded for a Pipeline with a 30-day priority fetch period, created on October 16, 2026:
| Pipeline Run | Job | Data Loaded |
|---|---|---|
| First run | Priority sync | Data from September 16, 2026, to October 16, 2026, for the priority objects. |
| First run | Backward sync | Data older than September 16, 2026, for the priority objects, and all the data for the remaining objects, up to the backward sync duration. |
| Second run | Incremental job | Data created or updated since the first run. |
| Second run | Backward sync | The remaining older data, if any, up to the backward sync duration. |
| Subsequent runs | Incremental job, followed by a backward sync until all the older data is loaded | New and updated data, and the remaining older data. |
If you add an object to your Pipeline after it is created, or resync an object, Hevo ingests its data through a regular historical load, and not on a priority-first basis.
Viewing Priority-First Sync Jobs
You can view these jobs in the Job History tab of your Pipeline. The priority sync and the backward sync are displayed as Historical jobs, and the jobs that ingest your new and updated data are displayed as Incremental jobs. When you resync the Pipeline, the two jobs are displayed as Resync jobs.
In the first run of the Pipeline, both the jobs start at the same time. To identify them, click the job. The priority sync lists only the priority objects and their child objects, and the backward sync lists all the objects in your Pipeline.
In the following image, the two historical jobs started at 10:18 AM. The job that ingested 615.48K Events is the priority sync, and the one that ingested 133.76K Events is the backward sync. The job that started at 11:18 AM is the incremental job of the next run.

Revision History
Refer to the following table for the list of key updates made to this page:
| Date | Release | Description of Change |
|---|---|---|
| Oct-22-2026 | NA | New document. |