- 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
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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
- 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
- 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
-
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
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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
-
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 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
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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 2.30 (Oct 21-Nov 18, 2024)
- Release 2.29 (Sep 30-Oct 22, 2024)
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2024 Releases
- 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)
-
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)
-
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
Google Cloud SQL Server
Google Cloud SQL Server is a fully-managed database service that helps you set up, maintain, manage, and administer your SQL Server relational databases on Google Cloud Platform.
You can ingest data from your Google Cloud SQL Server database using Hevo Pipelines and replicate it to a Destination of your choice.
Prerequisites
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The Google Cloud SQL Server instance is running. To check this, access your Google Cloud SQL Instances page and look for an Active indication next to the instance ID.
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The SQL Server version is 2017.
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You are assigned the Team Administrator, Team Collaborator, or Pipeline Administrator role in Hevo, to create the Pipeline.
Perform the following steps to configure your Google Cloud SQL Server Source:
Whitelist Hevo’s IP Addresses
You need to whitelist the Hevo IP address for your region to enable Hevo to connect to your Google Cloud SQL Server database. To do this:
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Access the Google Cloud SQL Instances page and click the Instance ID that you want to use.
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In the left navigation pane, click Connections.
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In the Networking tab, select the Public IP check box and then click + ADD A NETWORK.
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Specify the following in the Edit Network section:
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Name: A name for this connection. For example, all or Hevo IP address.
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Network: The IP address of the site to grant access to. Specify 0.0.0.0/0 to authorize all sites or your region’s IP address to specifically whitelist Hevo’s IP address.
This adds the IP address to the list of Authorized networks.
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(Optional) Click + Add network to add another IP address.
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Click Save.
Create a User and Grant Privileges
Option 1. Configuring the user account using Google Cloud console
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Access the Google Cloud SQL Instances page and click the master Google Cloud SQL Server instance.
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In the left navigation pane, under Connections, click the Users tab, and then, click + ADD USER ACCOUNT.
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Specify the user account information and click ADD.
You will specify this username and password while creating your Hevo Pipeline.
Option 2. Configuring the user account using SQL Server client
Log in to your SQL Server instance as masteruser
using your preferred SQL Server client tool, and enter the following commands:
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Log in to the database where you want to add the user:
USE <database_name>;
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(Optional) Create a login user.
Note: You can skip this step if you want to use the existing login user to create a new database user.
CREATE LOGIN <login_user> WITH PASSWORD = '<password>';
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Create a new database user and grant
read
privileges:CREATE USER hevo for login <master_username>; EXEC sp_addrolemember 'db_datareader', 'hevo';
Retrieve the Configuration Details (Optional)
Refer to the steps below to gather the configuration details required to create your Hevo Pipeline:
1. Retrieve the hostname and port number
Note: Following is an example of Google Cloud SQL Server hostname and port number:
Host : 35.220.150.0
Port : 1433
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Access the Google Cloud SQL Instances page.
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Locate the hostname of the master instance under the Public IP address column.
The default port value is 1433.
You will specify these while creating your Hevo Pipeline.
2. Retrieve the username and password
To retrieve your username and password, follow the steps in section, Create a User and Grant Privileges.
3. Retrieve the database names
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Access the Google Cloud SQL Instances page.
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Click your database instance, and then, click the Databases tab.
On this page, you can locate the name of your database under the Name column.
Specify Google Cloud SQL Server Connection Settings
Perform the following steps to configure Google Cloud SQL Server as a Source in Hevo:
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Click PIPELINES in the Navigation Bar.
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Click + CREATE PIPELINE in the Pipelines List View.
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On the Select Source Type page, select Google Cloud SQL Server.
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On the Configure your Google Cloud SQL Server Source page, specify the following:
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Pipeline Name: A unique name for the Pipeline, not exceeding 255 characters.
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SQL Server Host: SQL Server host’s IP address or DNS.
The following table lists a few examples of SQL Server hosts:
Variant Host Amazon RDS SQL Server ms-sql-server-1.xxxxx.rds.amazonaws.com Azure MS SQL mssql.database.windows.net Generic MS SQL 10.123.10.001 or mssql.westeros.inc Google Cloud SQL Server 35.220.150.0 Note: For URL-based hostnames, exclude the http:// or https:// part. For example, if the hostname URL is https://mssql.database.windows.net, enter mssql.database.windows.net.
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SQL Server Port: The port on which your SQL Server is listening for connections. Default value: 1433.
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SQL Server User: The read-only user who has the permissions to read tables in your database.
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SQL Server Password: The password for the read-only user.
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Select an Ingestion Mode: The desired mode by which you want to ingest data from the Source. You can expand this section by clicking SEE MORE to view the list of ingestion modes to choose from. Default value: Change Tracking. The available ingestion modes are Change Tracking, Table, and Custom SQL.
Depending on the ingestion mode you select, you must configure the objects to be replicated. Refer to section, Object and Query Mode Settings for the steps to do this.
Note: For Custom SQL ingestion mode, all Events loaded to the Destination are billable.
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Database Name: The database that you wish to replicate.
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Schema Name: The schema that holds the tables to be replicated. Default value: dbo.
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Connect through SSH: Enable this option to connect to Hevo using an SSH tunnel, instead of directly connecting your SQL Server database host to Hevo. This provides an additional level of security to your database by not exposing your SQL Server setup to the public. Read Connecting Through SSH.
If this option is disabled, you must whitelist Hevo’s IP addresses. Refer to the content for your SQL Server variant for steps to do this.
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Advanced Settings:
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Include New Tables in the Pipeline: Applicable for all ingestion modes except Custom SQL. If enabled, Hevo automatically ingests data from tables created after the Pipeline has been built. If disabled, the new tables are listed in the Pipeline Detailed View in Skipped state, and you can manually include the ones you want and load their historical data. You can include these objects post-Pipeline creation to ingest data.
You can change this setting later.
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-
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Click TEST CONNECTION. This button is enabled once you specify all the mandatory fields. Hevo’s underlying connectivity checker validates the connection settings you provide.
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Click TEST & CONTINUE to proceed for setting up the Destination. This button is enabled once you specify all the mandatory fields.
Object and Query Mode Settings
Once you have specified the Source connection settings in Step 4 above, do one of the following:
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For Pipelines configured with the Change Tracking ingestion mode:
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On the Select Objects page, select the objects you want to replicate.
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Click CONTINUE. This button is enabled once you select at least one object for which Change Tracking is enabled.
Note:
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Each object represents a table in your database.
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You must enable Change Tracking for the objects you want to ingest data from. If disabled, Hevo adds these objects to your Pipeline in the SKIPPED state.
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For customers signing up after Release 2.19, Hevo automatically uses the Unique Incrementing Append Only (UIAO) query mode for the objects that contain a unique column. For the others, it ingests data using the Full Load query mode.
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-
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For Pipelines configured with the Table ingestion mode:
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On the Select Objects page, select the objects you want to replicate and click CONTINUE.
Note: Each object represents a table in your database.
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On the Configure Objects page, specify the query mode you want to use for each selected object.
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For Pipelines configured with the Custom SQL ingestion mode:
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On the Provide Query Settings page, enter the custom SQL query to fetch data from the Source.
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In the Query Mode drop-down, select the query mode, and click CONTINUE.
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Data Replication
For Teams Created | Default Ingestion Frequency | Minimum Ingestion Frequency | Maximum Ingestion Frequency | Custom Frequency Range (in Hrs) |
---|---|---|---|---|
Before Release 2.21 | 15 Mins | 5 Mins | 24 Hrs | 1-24 |
After Release 2.21 | 6 Hrs | 30 Mins | 24 Hrs | 1-24 |
Note: The custom frequency must be set in hours as an integer value. For example, 1, 2, or 3 but not 1.5 or 1.75.
- Historical Data: In the first run of the Pipeline, Hevo ingests all available data for the selected objects from your Amazon Redshift database.
- Incremental Data: Once the historical load is complete, data is ingested as per the ingestion frequency.
Additional Information
Read the detailed Hevo documentation for the following related topics:
Limitations
- Hevo does not support data replication from temporary tables and views.
Revision History
Refer to the following table for the list of key updates made to this page:
Date | Release | Description of Change |
---|---|---|
Oct-22-2024 | NA | Updated section, Whitelist Hevo’s IP Addresses as per the latest Google Cloud SQL Server UI. |
Apr-29-2024 | NA | Updated section, Specify Google Cloud SQL Server Connection Settings to include more detailed steps. |
Mar-05-2024 | 2.21 | Added the Data Replication section. |
Jan-15-2024 | NA | Added section, Limitations. |
Jan-10-2024 | 2.19 | Updated section, Object and Query Mode Settings as per the latest Hevo functionality. |
Nov-03-2023 | NA | Added section, Object and Query Mode Settings. |
Apr-21-2023 | NA | Updated section, Specify Google Cloud SQL Server Connection Settings to add a note to inform users that all loaded Events are billable for Custom SQL mode-based Pipelines. |
Mar-09-2023 | 2.09 | Updated section, Specify Google Cloud Server Connection Settings to mention about SEE MORE in the Select an Ingestion Mode section. |
Dec-19-2022 | 2.04 | Updated section, Specify Google Cloud SQL Server Connection Settings to add information that you must specify all fields to create a Pipeline. |
Dec-07-2022 | 2.03 | Updated section, Specify Google Cloud SQL Server Connection Settings to mention about including skipped objects post-Pipeline creation. |
Dec-07-2022 | 2.03 | Updated section, Specify Google Cloud SQL Server Connection Settings to mention about the connectivity checker. |
Jun-28-2022 | NA | Removed section, Source Considerations. |
Apr-21-2022 | 1.86 | Updated section, Specify Google Cloud SQL Server Connection Settings. |
Jul-26-2021 | 1.68 | Added a note for the SQL Server Host field. |
Jul-12-2021 | NA | Added section, Specify Google Cloud SQL Server Connection Settings. |
Feb-22-2021 | 1.57 | New Document |