Release Version 2.12

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To know the list of features and integrations we are working on next, read our Upcoming Features page!

In this Release

• New and Changed Features
• Fixes and Improvements
• Documentation Updates

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New and Changed Features

Destinations

• Check for Mandatory Field Entries during Destination Setups

  • Enhanced the Destination configuration user interface to enable the TEST CONNECTION and SAVE & CONTINUE buttons only after all the mandatory fields are filled in by a user. As a result, users encounter fewer errors while testing the connection. The feature is currently applicable to all Destinations except Google BigQuery.

Pipelines

• IAM Role-based Authentication in Amazon CloudWatch

  • Enhanced the Amazon CloudWatch integration to provide support for connecting to Amazon CloudWatch using the IAM credentials of your AWS account. If you do not want to provide your access credentials, you can now enable the required access via IAM roles and use these to connect to the Source.

    

    Read Amazon CloudWatch.

Sources

• IAM Role-based Authentication in Amazon DynamoDB

  • Enhanced the Amazon DynamoDB integration to provide support for connecting using the IAM credentials of your AWS account. If you do not want to provide your access credentials, you can now enable the required access via IAM roles and use these to connect to the Source.

    

    Read Amazon DynamoDB.

Fixes and Improvements

Sources

• Improved Handling of Decimal Values in PostgreSQL Source

  • Fixed an issue in the PostgreSQL integration to correctly handle decimal values with more than nine decimal digits by rounding off the data to nine decimal places. This fix resolves Pipeline errors when ingesting data from a Source table whose definition does not specify a scale (number of digits to the right of the decimal point) for a decimal column.

• Ingesting Data for Associations of Custom Objects in HubSpot

  • Enhanced the integration to support ingestion of data for associations of custom objects. This enables you to track objects that are associated with your custom objects. This feature is applicable to all Pipelines created from Release 1.98 onwards and is currently available on request. Contact Hevo Support to enable it for your team.

User Experience

• Replaced Mentions of Asset Palette with Navigation Bar

  • Updated the pages in the documentation site to replace mentions of Asset Palette with Navigation Bar for ease of understanding.

Documentation Updates

The following pages have been created, enhanced, or removed in Release 2.12:

Activate

• Google BigQuery

Data Ingestion

• Ingestion Modes

Destinations

• Amazon Aurora MySQL

• Amazon Redshift

• Azure Synapse Analytics

• Databricks

• MySQL

• PostgreSQL

• Snowflake

• SQL Server

Getting Started

• Activity Logs - CloudWatch Sync

• Connection Options

Pipelines

• Pipeline FAQs

  • How can I make sure that each record is loaded only once?

  • How do I set a field as a primary key to avoid duplication?

• Transformations

  • Python Code-Based Transformations

  • Python Modules and Functions Supported in Code-Based Transformations (New)

  • TimeUtils

    • Convert date string to required format (New)

    • Convert date to required format (New)

    • Convert datetime string to required format (New)

    • Convert epoch time to a date (New)

    • Convert epoch time to a datetime (New)

    • Convert epoch to required format (New)

    • Convert epoch to a time (New)

    • Get time difference (New)

    • Parse date string to date (New)

    • Parse date string to datetime format (New)

    • Parse date string to time (New)

  • Transformation FAQs

    • Can I import standard Python libraries in Transformation? (Removed, and the content merged into Python Code-Based Transformations)

Sources

• Amazon DynamoDB

• Amazon Redshift

• Firebase Analytics (New)

• Google Search Console

• HubSpot

• MySQL

  • Amazon Aurora MySQL

  • Azure MySQL

  • Amazon RDS MySQL

  • Generic MySQL

  • Google Cloud MySQL

  • MariaDB MySQL

• Oracle

  • Amazon RDS Oracle

  • Generic Oracle

• PostgreSQL

  • Amazon Aurora PostgreSQL

  • Amazon RDS PostgreSQL

  • Azure PostgreSQL

  • Generic PostgreSQL

  • Google Cloud PostgreSQL

  • Heroku PostgreSQL

• SQL Server

  • Amazon RDS SQL Server

  • Azure SQL Server

  • Generic SQL Server

  • Google Cloud SQL Server