- About Hevo
- Hevo Features
- Hevo System Architecture
- Core Concepts
- Free Trials
- Regulatory Compliance
- Hevo Support
- General FAQs
- Getting Started
- Creating an Account in Hevo
- Connection Options
- Familiarizing with the UI
- Creating your First Pipeline
- Data Loss Prevention and Recovery
- Data Ingestion
- Types of Data Synchronization
- Ingestion Modes and Query Modes for Database Sources
- Ingestion and Loading Frequency
- Ingestion Frequency and Data Synchronization
- Data Ingestion Statuses
- Deferred Data Ingestion
- Handling of Primary Keys
- Handling of Updates
- Handling of Deletes
- Hevo-generated Metadata
- 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
- Data Loading Statuses
- Data Spike Alerts
- Name Sanitization
- Table and Column Name Compression
- Parsing Nested JSON Fields in Events
- Data Flow in a Pipeline
- Familiarizing with the Pipelines UI
Working with Pipelines
- Best Practices for Creating Database Pipelines
- Creating a Pipeline
- Connectivity Check for RDBMS Sources
- Scheduling a Pipeline
- Modifying a Pipeline
- Prioritizing a Pipeline
- Viewing Pipeline Progress
- Pausing and Deleting a Pipeline
- Log-based Pipelines
- Troubleshooting Data Replication Errors
- Managing Objects in Pipelines
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
- 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
- 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
- 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
- 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
- Activity Log
- Does creation of Pipeline incur cost?
- Why are my new Pipelines in trial?
- 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 delete skipped objects in a Pipeline?
- Can I change the Destination post-Pipeline creation?
- How does changing the query mode affect data ingestion?
- 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 sort Event Types listed in the Schema Mapper?
- 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 restart the historical load for all the objects?
- How do I set a field as a primary key?
- How can I load only filtered Events to the Destination?
- How do I ensure that records are loaded only once?
- Why do the Source and the Destination events count differ?
- Events Usage
- Free Sources
Databases and File Systems
- Data Warehouses
- Connecting to a Local Database
- Amazon DocumentDB
- Amazon DynamoDB
- Generic MongoDB
- MongoDB Atlas
- Support for Multiple Data Types for the _id Field
- Example - Merge Collections Feature
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
- Amazon RDS SQL Server
- Azure SQL Server
- Google Cloud SQL Server
- Generic SQL Server
- Troubleshooting SQL Server
- SQL Server FAQs
- Amazon Aurora MySQL
- Amazon RDS MySQL
- Azure MySQL
- Google Cloud MySQL
- Generic MySQL
- MariaDB 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
- Amazon Aurora PostgreSQL
- Amazon RDS PostgreSQL
- Azure PostgreSQL
- Google Cloud PostgreSQL
- Generic PostgreSQL
- Heroku 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
- Amazon S3
- Azure Blob Storage
- FTP / SFTP
- Google Cloud Storage (GCS)
- Google Drive
- Google Sheets
- Android SDK
- Writing JSONPath Expressions
REST API FAQs
- Why does my REST API token keep changing?
- Can I use a bearer authorization token for authentication?
- Does Hevo’s REST API support API chaining?
- What is the maximum payload size returned by a REST API?
- How do I split an Event into multiple Event Types?
- How do I split multiple values in a key into separate Events?
- Jira Cloud
- Finance & Accounting Analytics
- Apple Search Ads
- Facebook Ads
- Facebook Page Insights
- Firebase Analytics
- Google Campaign Manager
- Google Ads
- Google Analytics
- Google Analytics 4
- Google Analytics 360
- Google Play Console
- Google Search Console
- Instagram Business
- LinkedIn Ads
- Microsoft Advertising
- Pinterest Ads
- SendGrid Webhook
- Salesforce Marketing Cloud
- Snapchat Ads
- TikTok Ads
- Twitter Ads
- YouTube Analytics
- Product Analytics
Sales & Support Analytics
- Help Scout
- Hub Planner
- Toggl Track
- From how far back can the Pipeline ingest data?
- Can I connect to a Source not listed in Hevo?
- Can I connect a local database as a Source?
- How can I push data to Hevo API?
- How do I connect a CSV file as a Source?
- Why are my selected Source objects not visible in the Schema Mapper?
- How can I transfer Excel files using Hevo?
- How does the Merge Table feature work?
- Familiarizing with the Destinations UI
- Amazon Aurora MySQL
- SQL Server
- Connecting to a Local Database
- Limitations of using MySQL as a Destination
- Structure of Data in the Amazon Redshift Data Warehouse
- Loading Data to an Amazon Redshift Data Warehouse
- Troubleshooting Amazon Redshift Destination
- Amazon Redshift FAQs
- Azure Synapse Analytics
- Clustering in BigQuery
- Partitioning in BigQuery
- Loading Data to a Google BigQuery Data Warehouse
- Near Real-time Data Loading using Streaming
- Troubleshooting Google BigQuery
- Google BigQuery FAQs
- Hevo Managed Google BigQuery
- Structure of Data in the Snowflake Data Warehouse
- Loading Data to a Snowflake Data Warehouse
- Troubleshooting Snowflake
- Snowflake FAQs
- Amazon Redshift
- Can I move data between SaaS applications using Hevo?
- 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?
- How do I resolve duplicate records in the Destination table?
- How do I enable or disable deduplication of records?
- 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?
- Can I load data to a specific Destination table?
- How do I filter out specific fields before loading data?
- How do I sort the data in the Destination?
- dbt™ Models
- Familiarizing with the Models UI
- Types of Models
- Key Features
- Working with SQL Models
- Previewing a Model
- Viewing the Query History
- Legacy Models
- Models FAQs
- Account Management
- Personal Settings
- Team Settings
- Pricing Plans
- Time-based Events Buffer
- Setting up Pricing Plans, Billing, and Payments
- On-Demand Purchases
- Billing Alerts
- Viewing Billing History
- Billing Notifications
- Can I get a plan apart from the Starter plan?
- Are free trial Events charged once I purchase a plan?
- For how long can I stay on the Free plan?
- How can I upgrade my plan?
- Is there a discount for non-profit organizations?
- Can I seek a refund of my payment?
- Do ingested Events count towards billing?
- Will Pipeline get paused if I exceed the Events quota?
- Will the initial load of data be free?
- Does the Hevo plan support multiple Destinations?
- Do rows loaded through Models count in my usage?
- Is Hevo subscription environment-specific?
- Can I pause billing if I have no active Pipelines?
- Can you explain the pricing plans in Hevo?
- Where do I get invoices for payments?
- Account Suspension and Restoration
- Account Management FAQs
- Activate Concepts
- Familiarizing with the Activate UI
- Working with Activate
- Activate Warehouses
- Activate Targets
- Release Notes
- 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
- 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)
- 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
Marketo is a marketing automation platform used by B2B and B2C companies to manage and deliver personalized multi-channel programs and campaigns to prospects and customers. Marketo enables companies to curate their raw user data and create programs and focussed campaigns for different marketing activities, from lead generation to marketing ROI measurement, across multiple channels.
With the help of Pipelines in Hevo, you can synchronize Marketo with a database or data warehouse Destination to always have access to the latest data, which you can feed into your enterprise BI solution for custom reporting and analysis. Hevo Pipelines use Marketo’s bulk (preferred) and REST APIs to fetch both historical and changed data, which you can replicate to the Destination after performing any necessary transformations on it.
For creating Pipelines using this Source, Hevo provides you a fully managed BigQuery data warehouse as a possible Destination. This option remains available till the time you set up your first BigQuery Destination irrespective of any other Destinations that you may have. With the managed warehouse, you are only charged the cost that Hevo incurs for your project in Google BigQuery. The invoice is generated at the end of each month and payment is recovered as per the payment instrument you have set up. You can now create your Pipeline and directly start analyzing your Source data. Read Hevo Managed Google BigQuery.
- You are assigned the Team Administrator, Team Collaborator, or Pipeline Administrator role in Hevo to create the Pipeline.
Configuring Marketo as a Source
To configure Marketo as a Source:
Obtain authenticated access credentials for your Marketo instance.
Note: While creating a new role, you must either individually select all
Read-Onlyprivileges or provide all Access-API privileges.
Click PIPELINES in the Navigation Bar.
Click + CREATE in the Pipelines List View.
In the Select Source Type page, select Marketo.
In the Configure your Marketo Source page, specify the following:
Pipeline Name: A unique name for the Pipeline, not exceeding 255 characters.
Client ID - Available at the newly created service.
Client Secret - Available at the newly created service.
Endpoint - The base URL used to make all the API calls.
Identity Endpoint - The endpoint used to retrieve access tokens using the Client ID and Client Secret.
Click TEST & CONTINUE.
Proceed to configuring the data ingestion and setting up the Destination.
Note: If IP restriction is enabled in your Marketo account, you must either whitelist Hevo IPs or disable IP restriction to allow Hevo to make API calls.
Marketo API Limits
Marketo imposes strict limits on the API calls you can make within a given time frame to retrieve the data. Some of these include:
Rate Limit: Maximum of 100 API calls per 20 seconds per instance.
Concurrency Limit: Maximum of 10 concurrent API calls.
Daily Quota: Up to 50,000 API calls per day with a max export of 500 MB for bulk jobs for paid subscription (quota resets daily at midnight CST).
Read more about Marketo API limits.
Hevo Pipelines overcome these limitations by using Bulk APIs to fetch the data.
Data Ingestion using Bulk APIs
The Hevo connector uses Bulk APIs by default for all Marketo objects that allow this, namely, Program members, Activities and Leads. As a result, Hevo can minimize the number of API calls, while maximising the number of Events fetched per API call, and thereby, help you to remain within the imposed limits to the extent possible. This becomes specially useful while retrieving historical data.
Bulk APIs in Marketo uses the same permissions as the REST APIs, therefore, the job or API type that is running is transparent to you except for the API endpoint.
Compared to a REST API, for a bulk extract:
The Hevo connector submits the job for the data you need, with the required metadata, to Marketo.
Marketo queues and runs the job.
Hevo queries for the status intermittently and when the job completes, Hevo makes one single call to fetch the data, extract the input stream, and process the records in order.
See Appendix 1 - Destination Tables for the list of Marketo objects that allow bulk operations.
|Default Pipeline Frequency||Minimum Pipeline Frequency||Maximum Pipeline Frequency||Custom Frequency Range (Hrs)|
|3 Hrs||3 Hrs||48 Hrs||3-48|
Note: The custom frequency must be set in hours, as an integer value. For example, 1, 2, 3 but not 1.5 or 1.75.
Hevo ingests the data from Marketo as follows:
Historical Data: In the first run of the Pipeline, Hevo ingests the data of the past one year, a month at a time, for the selected objects using the Recent Data First approach.
Incremental Data: Once the historical load is complete, all new records are synchronized with your Destination as per the Pipeline frequency.
Data Refresh: The data for the past three months is ingested on every run to ensure that your data is up to date and any data freshness issues are overcome.
Refer to the table below for the type of data that is fetched for each object.
|Data Type||Object Names||Schedule||Additional Information|
|Historical||Activities||During the first run of the Pipeline|
|Incremental||Activities, Activity Types, Campaigns, Leads, Programs||During each run of the Pipeline||For the Campaigns object, data for the past 12 months is fetched on the first run.|
|Refresh Data||Leads||Every 24 hours post-completion of ingestion||Ensures that leads, opportunity, opportunity roles, and salespersons data is up to date.|
Note: The time taken for the Historical data load is determined by the amount of data and processing time for the ingestion from Marketo.
Schema and Primary Keys
Hevo uses the following schema to upload the records in the Destination database:
The following is the list of tables (objects) that are created at the Destination when you run the Pipeline:
|Activities||Incremental||Contains details of all the events or happenings regarding leads in your Marketo account. For example, opening an email and clicking a link, submitting a form, and visiting a web page.|
|Activity New Lead||Full Load||Contains details about a new lead added to the Marketo database.|
|Campaign||Incremental||Contains details of the events executed to increase engagement and streamline communications with leads and existing customers.|
|Leads||Incremental||Contains details of prospective customers.|
|List||Full Load||Contains details of the leads present in a database in the Marketo account.|
|List Membership||Incremental||Contains details of the lists that a lead is a member of.|
|Opportunity Role||Incremental||Contains details of the relationship between an opportunity and a lead and the function of this lead in the organization.|
|Opportunity||Incremental||Contains details of a potential sales deal or a lead that is identified as a potential customer.|
|Program Membership||Full Load||Contains details of the membership of a person in different programs.|
|Program||Full Load||Contains details of the marketing activities organized and executed in an organization. For example, campaigns, events, webinars, and email drip campaigns.|
|Sales Person||Incremental||Contains details of the sales people who are in charge of leads, and who remain in contact with them for selling the product.|
|Smart List||Incremental||Contains the list of specific leads and groups that can be searched in your Marketo account using filters.|
Read the detailed Hevo documentation for the following related topics:
Refer to the following table for the list of key updates made to this page:
|Date||Release||Description of Change|
|Feb-07-2023||2.07||Updated section, Data Model to add the List and List Membership objects.
- Updated section, Schema and Primary Keys to add the new ERD link with the List and List Membership objects.
|Dec-07-2022||NA||Updated section, Data Replication to reorganize the content for better understanding and coherence.|
|Oct-25-2021||NA||Added the Pipeline frequency information in the Data Replication section.|