- 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
-
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
-
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
-
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
-
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 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 2.31 (Nov 18-Dec 16, 2024)
- Release 2.30 (Oct 21-Nov 18, 2024)
-
2024 Releases
- Release 2.29 (Sep 30-Oct 22, 2024)
- 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)
-
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
-
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
FTP / SFTP
You can load data from files in an FTP location into your Destination database or data warehouse using Hevo Pipelines.
Hevo automatically unzips any Gzipped files on ingestion. Further, files are re-ingested if updated, as it is not possible to identify individual changes.
As of Release 1.66, __hevo_source_modified_at
is uploaded to the Destination as a metadata field. For existing Pipelines that have this field:
-
If this field is displayed in the Schema Mapper, you must ignore it and not try to map it to a Destination table column, else the Pipeline displays an error.
-
Hevo automatically loads this information in the
__hevo_source_modified_at
column, which is already present in the Destination table.
You can, however, continue to use __hevo_source_modified_at
to create transformations using the function event.getSourceModifiedAt()
. Read Metadata Column __hevo_source_modified_at
.
Existing Pipelines that do not have this field are not impacted.
Configuring FTP/SFTP as a Source
Perform the following steps to configure FTP/SFTP as the Source in your Pipeline:
-
Click PIPELINES in the Navigation Bar.
-
Click + CREATE PIPELINE in the Pipelines List View.
-
In the Select Source Type page, select FTP/SFTP.
-
In the Configure your FTP/SFTP Source page, specify the following:
-
Pipeline Name: A unique name for the Pipeline, not exceeding 255 characters.
-
Type: The network protocol for ingesting files. For example, FTP (File Transfer Protocol).
-
Host: The IP address or the DNS for your network protocol location.
-
Port: The port on which your network protocol server is listening for connections. Default value: 21.
-
User: The user ID for logging in to the network protocol server.
-
Password: The password of the user logging in to the network protocol server.
Note: This field is optional if you selected Type as SFTP above. However, you must add the public key displayed on the UI to the
.ssh/authorized\_keys
file on your SFTP server. -
Path Prefix: The prefix of the path for the directory that contains your data. By default, the files are listed from the root of the directory.
-
File Format: The format of the data file in the Source. Hevo supports the CSV, JSON, TSV, and XML file formats to ingest data.
Note: You can select only one file format at a time. If your Source data is in a different format, you can export the data to either of the supported formats and then ingest the files.
Based on the format you select, you must specify some additional settings:
-
Field Delimiter: The character on which the fields in each line are separated. For example,
\t
or,
.This field is visible only for CSV data.
-
Treat first row as column headers: If enabled, Hevo identifies the first row in your CSV file and uses it as a column header rather than an Event.
If disabled, and if your Source data file does not contain column headers, Hevo automatically creates them during ingestion. Default setting: Enabled. Refer to section, Example.
This field is visible only for CSV data.
-
Create Events from child nodes: If enabled, Hevo loads each node present under the root node in the XML file as a separate Event.
If disabled, Hevo combines and loads all nodes present in the XML file as a single Event.
This field is visible only for XML data.
-
-
Include compressed files: If enabled, Hevo also ingests the compressed files of the selected file format from the folders. Hevo supports the tar.gz and zip compression types only.
If disabled, Hevo does not ingest any compressed file present in the selected folders.
This field is visible for all supported data formats.
-
Create Event Types from folders: If enabled, Hevo ingests each subfolder as a separate Event Type.
Note: Files lying at the prefix path (and not in a subdirectory) are ignored.
If disabled, Hevo merges subfolders into their parent folders and ingests them as one Event Type.
This field is visible for all supported data formats.
-
Connect Through SSH: Enable this option to connect to Hevo using an SSH tunnel, instead of directly connecting your network protocol host to Hevo. This provides an additional level of security to your database by not exposing your network protocol setup to the public. Read Connecting Through SSH.
If this option is disabled, you must whitelist Hevo’s IP addresses to allow Hevo to connect to your network protocol host.
-
Convert date/time format fields to timestamp: If enabled, Hevo converts the date/time format within the files of selected folders to a timestamp. For example, the date/time format 07/11/2022, 12:39:23 converts into timestamp 1667804963.
If disabled, Hevo ingests the datetime fields in the original format.
This field is visible for all supported data formats.
-
-
Click TEST & CONTINUE.
-
Proceed to configuring the data ingestion and setting up the Destination.
Data Replication
For Teams Created | Default Ingestion Frequency | Minimum Ingestion Frequency | Maximum Ingestion Frequency | Custom Frequency Range (in Hrs) |
---|---|---|---|---|
Before Release 2.21 | 5 Mins | 5 Mins | 3 Hrs | NA |
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.
Additional Information
Read the detailed Hevo documentation for the following related topics:
Example: Automatic Column Header Creation for CSV Tables
Consider the following data in CSV format, which has no column headers.
CLAY COUNTY,32003,11973623
CLAY COUNTY,32003,46448094
CLAY COUNTY,32003,55206893
CLAY COUNTY,32003,15333743
SUWANNEE COUNTY,32060,85751490
SUWANNEE COUNTY,32062,50972562
ST JOHNS COUNTY,846636,32033,
NASSAU COUNTY,32025,88310177
NASSAU COUNTY,32041,34865452
If you disable the Treat first row as column headers option, Hevo auto-generates the column headers, as seen in the schema map here:
The record in the Destination appears as follows:
See Also
Revision History
Refer to the following table for the list of key updates made to this page:
Date | Release | Description of Change |
---|---|---|
Mar-05-2024 | 2.21 | Updated the ingestion frequency table in the Data Replication section. |
Sep-21-2023 | NA | Updated section, Configuring FTP/SFTP as a Source for better clarity. |
Nov-08-2022 | NA | Updated section, Configuring FTP/SFTP as a Source to add information about the Convert date/time format fields to timestamp option. |
Sep-21-2022 | NA | Added a note in section, Configuring FTP / SFTP as a Source. |
Apr-11-2022 | 1.86 | Updated section, Configuring FTP/SFTP as a Source to reflect support for TSV file format. |
Mar-21-2022 | 1.85 | Removed section, Limitations as Hevo now supports UTF-16 encoding format for CSV files. |
Oct-25-2021 | NA | Added the section, Data Replication. |
Jun-28-2021 | 1.66 | Updated the page overview with information about __hevo_source_modified_at being uploaded as a metadata field from Release 1.66 onwards. |
Feb-22-2021 | NA | Added the limitation about Hevo not supporting UTF-16 encoding format for CSV data. |