- Introduction
- 
Getting Started
  
      
- Creating an Account in Hevo
- Subscribing to Hevo via AWS 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
- Sources
- Destinations
- Alerts
- Custom Connectors
- Releases
 
- 
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?
 
 
- 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
- 
    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
- 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
- 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- Release 2.41.1 (Oct 06-13, 2025)
- Release 2.41 (Sep 08-Oct 06, 2025)
- Release 2.40 (Aug 11-Sep 08, 2025)
- 2025 Releases
- 
    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)
 
 
- Early Access New
On-Demand Syncing Data in Edge Pipelines
On This Page
Edge Pipeline is now available for Public Review. You can explore and evaluate its features and share your feedback.
Hevo Edge Pipelines sync data ingested from your Source with the Destination as per the Pipeline sync schedule, which runs according to the configured frequency. However, there could be scenarios such as the following, when you may want the Pipeline to sync data outside of the schedule:
- 
    You created the Pipeline and need the data in your Destination at the earliest. 
- 
    You changed the Pipeline configuration to resolve any job failures and want the Pipeline to start replicating data, but the configured frequency is 24 hours or more. 
- 
    The Source or Destination was not available for reasons such as an outage or planned maintenance, causing the jobs to fail. 
- 
    You noticed a data mismatch between the Source and the Destination and want to replicate the data immediately to identify the data records and for troubleshooting. 
- 
    You included new objects in the Pipeline and need to load their data into the Destination. 
To handle such scenarios, Hevo allows you to sync or resync data for your Edge Pipeline on-demand.
Sync Now
The Sync Now action starts a job to sync incremental data from your Source with the Destination. To start this job for your Pipeline, do the following:
- 
    In the Pipelines List View, click the Edge tab and then click the Pipeline whose data you want to sync.  
- 
    In the Pipeline Summary bar, click the Kebab menu icon (  ) and click Sync Now. ) and click Sync Now. 
- 
    In the pop-up dialog, click SYNC NOW.  
After you click SYNC NOW, Hevo performs the following actions on your Edge Pipeline:
- 
    Check if any job is in progress and prompt to cancel the active job. You can then choose to cancel the active job and start a new sync. 
- 
    Start the incremental data sync from the last successful offset for all the objects included in the Pipeline. 
- 
    Start the historical data sync for newly included objects in the Pipeline. 
Resync Pipeline
The Resync Pipeline action allows you to restart the historical load for all the active objects in your Pipeline. Resyncing a Pipeline re-ingests historical data from the Source objects. However, the data existing in the corresponding Destination tables is only updated if changes are detected in the re-ingested data. Hevo also evolves the schemas of the Destination tables if any changes are detected in the mapping. Now, if any of the objects are blocked due to incompatible schema evolution, you can choose to drop the Destination tables during the resync operation for all the active objects in your Pipeline. In this case, Hevo drops and re-creates the Destination tables for all the active objects. Data from the Source objects is re-ingested and loaded into the newly created Destination tables.
Note: You can only resync a Pipeline that is ENABLED.
Perform the following steps to resync your Edge Pipeline:
- 
    In the Pipelines List View, click the Edge tab and then click the Pipeline that you want to resync.  
- 
    In the Pipeline Summary bar, click the Kebab menu icon (  ) and click Resync Pipeline. ) and click Resync Pipeline. 
- 
    In the Resync Pipeline pop-up window, do the following:  - 
        (Optional) Select the Enable Drop and Load check box if you want Hevo to re-create the Destination tables for all the active objects in your Pipeline during the resync operation. 
- 
        Click RESYNC PIPELINE to confirm the action. 
 
- 
        
After you click RESYNC PIPELINE, Hevo performs the following actions on your Edge Pipeline:
- 
    Move the Pipeline to the RESYNCING state. 
- 
    Cancel any actively running jobs in the Pipeline. 
- 
    Drop and re-create the resources in your Source system that Hevo uses while ingesting data, such as the replication slot in your PostgreSQL database. 
- 
    Refresh the Source and Destination schemas. 
- 
    Compare the refreshed schemas and evolve the schema of the Destination tables based on the detected changes. 
- 
    Optionally, drop and re-create the Destination tables if the drop-and-load option is selected. 
- 
    Start the historical data sync for all objects included in the Pipeline. After the historical data sync is successful, the incremental data sync is run on schedule as per the configured frequency. 
- 
    Move the Pipeline to the ENABLED state. 
Note: If any of the tasks fail, the Pipeline moves to the FAILED state. You can try enabling the Pipeline later, and if the issue persists, contact Hevo Support.