Pipelines

What is a Pipeline?

A Pipeline moves your data from a Source to a Destination.

Pipeline Components

A Pipeline has the following components:

• Source: A Source is a database, an API endpoint or a File Storage which has the data that you want to analyze. Hevo integrates with a variety of Sources. Complete documentation on using various Sources can be found here.
• Transformations: Transformations are used when you want to clean, enrich or transform your data before loading it to your Destination. Check out Transformations to know more.
• Schema Mapper: Schema Mapper lets you map you source schemas to tables in your Destination warehouse. Check out Schema Mapper to know more.
• Destination: Destination is a data warehouse or database where the data collected from Sources is stored. Various Destination supported by Hevo is listed here.

• Articles in this section
  • Familiarizing with the Pipelines UI
  • Pipeline Concepts
    • Pipeline Modes
    • Types of Data Synchronization
    • Pipeline Objects
      • Managing Objects in Pipelines
      • Query Modes for Ingesting Data from Relational Databases
    • Data Ingestion
      • Data Ingestion Statuses
      • Deferred Data Ingestion
    • Handling of Updates
    • Data Loss Prevention
    • Events
      • Ingestion Limits for Events
      • Loading Events in Batches
      • Failed Events in a Pipeline
        • Reasons for Event Failures
        • Resolving Event Failures
    • Parsing Nested JSON Fields in Events
    • Table and Column Name Compression
    • Hevo-generated Metadata
      • Metadata Column __hevo_database_name
      • Metadata Column __hevo_id
      • Metadata Column __hevo_source_modified_at
  • Working with Pipelines
    • Creating a Pipeline
    • Viewing Pipeline Progress
    • Scheduling a Pipeline
    • Modifying a Pipeline
      • Reauthorizing the Source Account
    • Prioritizing a Pipeline
    • Pausing and Deleting a Pipeline
    • Log-based Pipelines
      • Pausing a Log-based Pipeline
      • Handling Deletes in Log-based Pipelines
  • Transformations
    • Python Code-Based Transformations
      • Example - Splitting Nested Events into Multiple Events
      • API References
        • Event Object
        • TimeUtils
        • Utils
    • Drag and Drop Transformations
      • Transformations and Properties
      • Examples of Drag and Drop Transformations
    • Transformation Reference
      • Datetime Field Values
      • Operators
      • Rounding Modes
      • Text Casing
      • Values and Formulas
  • Schema Mapper
    • Using Schema Mapper
    • Mapping Statuses
    • Auto Mapping Event Types
      • Modifying Schema Mapping for Auto Mapped 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