- Introduction
- Getting Started
- Creating an Account in Hevo
- Subscribing to Hevo via AWS Marketplace
-
Connection Options
- Connecting Through SSH
- Connecting Through Reverse SSH Tunnel
- Connecting Through VPN
- Connecting Through Mongo PrivateLink
- Connecting Through AWS Transit Gateway
- Connecting Through AWS VPC Endpoint
- Connecting Through AWS VPC Peering
- Using Google Account Authentication
- How Hevo Authenticates Sources and Destinations using OAuth
- Reauthorizing an OAuth Account
- Familiarizing with the UI
- Creating your First Pipeline
- Data Loss Prevention and Recovery
- Data Ingestion
- 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
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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
-
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
- 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
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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
- Troubleshooting Database Sources
- 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 Campaign Manager
- 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
- Firebolt
- Google BigQuery
- Hevo Managed Google BigQuery
- Snowflake
-
Destination FAQs
- Can I change the primary key in my Destination table?
- How do I change the data type of table columns?
- 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 2.28.2 (Oct 07-14, 2024)
- Release 2.28.1 (Sep 30-Oct 07, 2024)
- Release 2.28 (Sep 02-30, 2024)
- 2024 Releases
-
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
- Upcoming Features
Data Loading
The data ingested from the Source is loaded to the Destination warehouse at each run of your Pipeline. In case your Events quota gets exhausted, the Events in the Pipeline are stored in a data warehouse till the time you purchase additional Events, upon which they are replayed. Read the data replication section of your Source to know its replication strategy.
By default, Hevo maintains any primary keys that are defined in the Source data, in the Destination tables.
You can load both types of data:
Data without Primary Keys
If primary keys are not present in the Destination tables, Hevo directly appends the data into the target tables. While this can result in duplicate Events occurring in the Destination, there is no resource overhead stemming from the data loading process.
Data with Primary Keys
If primary keys are present in the Source data but not enforceable on the Destination warehouse, as in the case of Google BigQuery, Amazon Redshift, and Snowflake, then, ensuring uniqueness of data is not possible by default. Hevo circumvents this lack of primary key enforcement and guarantees that no duplicate data is loaded to or exists in the Destination tables by:
-
Adding temporary Hevo-internal meta columns to the tables to identify eligible Events,
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Using specific queries to cleanse the data of any duplicate and stale Events,
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Adding metadata information to each Event to uniquely identify its ingestion and loading time
Note: These steps utilize your Destination system’s resources in terms of CPU usage for running the queries and additional storage utilization for the duration of processing of the data.
Additions to the Destination Schema
Irrespective of the type of data, Hevo adds the following columns to the Destination tables as part of the data loading process:
Metadata Column | Description |
---|---|
__hevo_ingested_at |
A timestamp applied to each Event during ingestion. This timestamp helps to verify that the ingested Event is more current than what already exists in the Destination. For example, by the time a failed Event is resolved and replayed, a more recent Event may already have been loaded to the Destination. Comparing the ingestion timestamp, the stale record can be discarded from the ingested data. The timestamp is also retained in the Destination table. |
__hevo_loaded_at |
A timestamp to indicate when data was inserted, updated, or deleted (delete flag updated) in the Destination table. The difference between __hevo_ingested_at and __hevo_loaded_at measures the total time taken by Hevo to process the respective Event and can be used to identify latency. |
__hevo__marked_deleted |
A column to logically represent a deleted Event. When an Event is deleted in the Source, it is not physically deleted from the Destination table during the data loading process. Instead, the logical column, __hevo__marked_deleted , is set to True for it. |
is_row_deleted |
A column to logically represent a data record that was deleted in the Stripe Source. Hevo ingests the deleted Event, sets the column, is_row_deleted to True for it, and loads it to the Destination table. |
deleted_timestamp |
A timestamp to indicate when the data was deleted in the Stripe Source. You can use the value of deleted_timestamp to identify the Stripe event from the events object that deleted the data. |
Note: Hevo also adds the internal columns __he__msg_seq_id
and __hevo__consumption_id
to the ingested data to help with the deduplication process; these columns are removed before the final step of loading data into the Destination tables.
See Also
Revision History
Refer to the following table for the list of key updates made to this page:
Date | Release | Description of Change |
---|---|---|
Apr-11-2022 | NA | - Reorganized content. - Added the metadata columns that Hevo generates to handle deletes in a Stripe Source to the Additions to the Destination Schema section. |
Mar-21-2022 | NA | New document. |