- 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
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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
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Edge
- Getting Started
- Data Ingestion
- Core Concepts
- Pipelines
- Sources
- Destinations
- Alerts
- Custom Connectors
- Releases
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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
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Transformations
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Python Code-Based Transformations
- Supported Python Modules and Functions
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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
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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
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Python Code-Based Transformations
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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
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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
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Sources
- Free Sources
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Databases and File Systems
- Data Warehouses
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Databases
- Connecting to a Local Database
- Amazon DocumentDB
- Amazon DynamoDB
- Elasticsearch
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MongoDB
- Generic MongoDB
- MongoDB Atlas
- Support for Multiple Data Types for the _id Field
- Example - Merge Collections Feature
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Troubleshooting MongoDB
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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
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Errors During Pipeline Creation
- SQL Server
-
MySQL
- Amazon Aurora MySQL
- Amazon RDS MySQL
- Azure MySQL
- Generic MySQL
- Google Cloud MySQL
- MariaDB MySQL
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Troubleshooting MySQL
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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
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PostgreSQL
- Amazon Aurora PostgreSQL
- Amazon RDS PostgreSQL
- Azure PostgreSQL
- Generic PostgreSQL
- Google Cloud PostgreSQL
- Heroku PostgreSQL
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Troubleshooting PostgreSQL
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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
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Errors during Pipeline creation
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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
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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
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Destinations
- Familiarizing with the Destinations UI
- Cloud Storage-Based
- Databases
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Data Warehouses
- Amazon Redshift
- Amazon Redshift Serverless
- Azure Synapse Analytics
- Databricks
- Google BigQuery
- 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
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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
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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
Offset and Latency of Jobs and Objects (Edge)
Edge Pipeline is now available for Public Review. You can explore and evaluate its features and share your feedback.
Hevo maintains an offset to identify the position till where the job has picked up Events for processing. The offset, which is a string of bytes, is maintained for each Source object. In the case of log-based Pipelines, the offset is the log sequence number (LSN). This LSN is converted to a human-readable format and displayed on the user interface (UI) as a time value, comprising the date and time in UTC. The offset is an indicator of the Pipeline’s progress.
The offset value is preserved while the job is ongoing. Once ingestion is completed, it is updated with the position of the last successfully processed Event. The subsequent job in the schedule processes Events with an offset higher than this value. In case a job fails or completes with failures, the next job starts from the offset of the last successfully processed Event. If the job did not ingest any data from the Source in the run, the offset value remains unchanged.
Offset in Log-Based Pipelines
In log-based Pipelines, Hevo records the offset for a historical job to help monitor the Pipeline’s progress. However, if transactions are being recorded in the database log, the offset visible on the UI may be more recent, or if the position of the last transaction in the log is too far, the offset may seem to be less. The offset for an incremental job is determined from the log position and is the same for all the objects in a job. When an object is resynced from the Object Config tab, its offset at the object level is changed to the position of the last successfully processed Event. The resync operation, however, does not affect the offset of that object in the incremental job or the data loaded to the corresponding Destination table.
To view the offset of the objects in a job, do the following:
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Log in to your Hevo account. By default, PIPELINES is selected in the Navigation Bar.
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In the Pipelines List View, click the Edge tab and then click your Pipeline to view the list of jobs created for it.

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In the list, click a job to open its details.
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In the Objects section, hover over the value in the Offset column of any object to view the current offset. For example, in the image below, the offset for all the objects is Sep 29, 2024, 20:40 (UTC).

Suppose the category object was resynced. As seen in the image below, its offset changed to Sep 29, 2024, 20:51 (UTC).

Job and Objects Latency
Latency is calculated as the difference between when the data was modified at the Source and when it was loaded to the Destination. It is also called data latency or end-to-end latency. Latency helps ascertain the freshness of data in the Destination. For example, if the latency is around an hour, then it could be that the data was ingested at least an hour ago. Hevo records the latency for a job as Max Latency, which is calculated when the entire batch of data has been loaded to the Destination. It is calculated as the maximum of latencies across all Source objects. Latency at the object level is determined as the difference between when the record was modified in the Source object and when it was loaded into the corresponding Destination table.
Latency metrics
Hevo provides certain metrics that can be used to determine the overall efficiency of your Pipeline. These metrics are applicable at the job and object levels. The metrics for an object are calculated using the values of some Hevo-generated metadata columns in the object and are persisted when the entire batch of data is loaded.
The following table lists the metrics and their definitions:
| Metric Name | Object Level | Job Level |
|---|---|---|
| Min Latency | The minimum of the latencies across all Events processed for an object. | The minimum of the latencies across all Source objects in a job. |
| Max Latency | The maximum of the latencies across all Events processed for an object. | The maximum of the latencies across all Source objects in a job. |
| Mean Latency | The mathematical average of the Min and Max latencies for an object. It is calculated as the difference between the average of all ingestion and load times for an object. | The mathematical average of the mean latencies across all Source objects in a job. |
Viewing the job and object latency
To view the latency of a job:
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Log in to your Hevo account. By default, PIPELINES is selected in the Navigation Bar.
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In the Pipelines List View, click the Edge tab and then click your Pipeline to view the list of jobs created for it.

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In the list, click any job whose Max Latency column is not empty to view its details.
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In the Job Summary section, hover over the value in the Max Latency field to view the Min, Mean, and Max latencies of that job.

As seen in the image above, the Min Latency is 10 min 55 sec, which is from object 2, and the Max Latency is 32 min 6 sec, which is from object 3.
To view the latency of an object:
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Log in to your Hevo account. By default, PIPELINES is selected in the Navigation Bar.
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In the Pipelines List View, click the Edge tab and then click your Pipeline to view the list of jobs created for it.

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In the Objects section of the job, hover over a non-empty value in the Max Latency column. The Min, Mean, and Max latencies of the object are displayed in the hover window.
As seen in the image below, for object 2, the Min Latency is 10 min 55 sec, the Mean Latency is 12 min 23 sec, and the Max Latency is 17 min 33 sec.
