- Introduction
- Getting Started
- Data Ingestion
- Data Loading
- Loading Data in a Database Destination
- Loading Data to a Data Warehouse
- Optimizing Data Loading for a Destination Warehouse
- Manually Triggering the Loading of Events
- Scheduling Data Load for a Destination
- Loading Events in Batches
- Name Sanitization
- Table and Column Name Compression
- Parsing Nested JSON Fields in Events
- Pipelines
- Data Flow in a Pipeline
- Ingestion Modes
- Familiarizing with the Pipelines UI
- Pipeline Objects
- Working with Pipelines
- Transformations
-
Schema Mapper
- Using Schema Mapper
- Mapping Statuses
- Auto Mapping Event Types
- Mapping a Source Event Type with a Destination Table
- Mapping a Source Event Type Field with a Destination Table Column
- Schema Mapper Actions
- Fixing Unmapped Fields
- Resolving Incompatible Schema Mappings
- Resizing String Columns in the Destination
- Schema Mapper Compatibility Table
- Failed Events in a Pipeline
- Pipeline FAQs
- Events Usage
- Sources
- Free Sources
- Analytics
- Collaboration
- CRM
- Data Warehouses
- Databases
- E-Commerce
- File Storage
- Finance & Accounting
-
Marketing
- AdRoll
- Apple Search Ads
- AppsFlyer
- Criteo
- Facebook Ads
- Facebook Page Insights
- Google Ads
- Google Campaign Manager
- Google Play Console
- Google Search Console
- HubSpot
- Instagram Business
- Klaviyo
- LinkedIn Ads
- Mailchimp
- Marketo
- Microsoft Advertising
- Outbrain
- Pardot
- Pinterest Ads
- Segment
- SendGrid
- SendGrid Webhook
- Salesforce Marketing Cloud
- Snapchat Ads
- Taboola
- Twitter Ads
- Streaming
- Source FAQs
- Destinations
- Transform
- Activate
- Alerts
- Account Management
- Troubleshooting
-
Troubleshooting Sources
- Troubleshooting Amazon DynamoDB
- Troubleshooting MongoDB
- Troubleshooting MS SQL
- Troubleshooting MySQL
- Troubleshooting Oracle
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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 during Pipeline creation
- Troubleshooting Salesforce
- Troubleshooting Destinations
-
Troubleshooting Sources
- Glossary
- Release Notes
- 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)
- 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)
- 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)
- Upcoming Features
Schema Mapper
Hevo ingests your data from Sources, applies transformations on it, and brings it to Schema Mapper. In Schema Mapper you can define how your data must be stored in the Destination.
You can use Schema Mapper to do the following:
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Map an incoming Event Type to a Destination table: All the data for that Event Type is stored in the mapped Destination Table.
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Omit unwanted fields from being stored in the Destination table: This is especially useful to hide sensitive information, such as, your user’s personal details and financial information. You can also omit large text fields like descriptions, summaries, and comments.
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Flatten nested objects into a de-normalized Destination table: Schema Mapper automatically suggests a de-normalized, flat structure for your incoming nested objects.
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Compress long names of Events and Event Types: Schema Mapper does this automatically to meaningfully modify the names to fit the character limit set for table and column names in the Destination.
In addition, Schema Mapper provides you the Auto Mapping feature, which:
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Automatically creates and manages all the mappings for you.
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Creates tables with compatible and optimal data types in your Destination warehouse, if none exist.
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Marks incompatible incoming Events as Failed for investigation.
- Articles in this section
- Using Schema Mapper
- Mapping Statuses
- Auto Mapping Event Types
- Mapping a Source Event Type with a Destination Table
- Mapping a Source Event Type Field with a Destination Table Column
- Schema Mapper Actions
- Fixing Unmapped Fields
- Resolving Incompatible Schema Mappings
- Resizing String Columns in the Destination
- Schema Mapper Compatibility Table