- Introduction
- Getting Started
- Data Ingestion
- 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
- Pipelines
- Data Flow in a Pipeline
- Familiarizing with the Pipelines UI
- Working with Pipelines
- Pipeline Objects
-
Transformations
- 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
-
Schema Mapper
- Using Schema Mapper
- Mapping Statuses
- Auto Mapping Event Types
- Mapping a Source Event Type Field with a Destination Table Column
- 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
- Troubleshooting Failed Events in a Pipeline
- Mismatch in Events Count in Source and Destination
-
Pipeline FAQs
- Does creation of Pipeline incur cost?
- Why are my new Pipelines in trial?
- Can multiple Sources connect to one Destination?
- Is my data stored after I delete a Pipeline?
- What happens if I re-create a deleted Pipeline?
- When should I pause vs delete my Pipeline?
- Why am I getting warnings while adding Pipelines?
- Why is there a delay in my Pipeline?
- Can I delete skipped objects in a Pipeline?
- How do I disable Auto Mapping?
- How do I change the ingestion frequency for tables?
- Can I change the Destination post-Pipeline creation?
- How do I change the query mode for my Pipelines?
- How does changing the query mode affect data ingestion?
- Why is my billable Events high with Delta Timestamp mode?
- How does the timing of Change Schedule work?
- 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?
- How do I include new tables in the Pipeline?
- Can I see the historical load progress?
- Why is my Historical Load Progress still at 0%?
- Why is the 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?
- How can I transfer Excel files using Hevo?
- How can I load an XML file from an S3 folder?
- 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
- Google Cloud MySQL
- Generic 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
- Google Cloud PostgreSQL
- Generic 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
- Apify
- Asana
- GitHub
-
Streaming
- Android SDK
- Kafka
-
REST API
- Writing JSONPath Expressions
-
REST API FAQs
- Why does my REST API token keep changing?
- Is it possible to use a Bearer Authorization token?
- 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?
- Webhook
- Jira Cloud
- Opsgenie
- PagerDuty
- Pingdom
- Trello
- Finance & Accounting Analytics
-
Marketing Analytics
- ActiveCampaign
- AdRoll
- Apple Search Ads
- AppsFlyer
- CleverTap
- Criteo
- Drip
- Facebook Ads
- Facebook Page Insights
- Freshsales
- Google Campaign Manager
- Google Ads
- Google Analytics
- Google Analytics 4
- Google Analytics 360
- Google Play Console
- Google Search Console
- HubSpot
- Instagram Business
- Klaviyo
- Lemlist
- LinkedIn Ads
- Mailchimp
- Mailshake
- Marketo
- Microsoft Advertising
- 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
- From how far back can the Pipeline ingest data?
- What is a free Source?
- Why am I unable to modify my OAuth Source connection settings?
- 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?
- Which file formats are supported by file storage-based Sources?
- Why are my selected Source objects not visible in the Schema Mapper?
- How does the Merge Table feature work?
- Destinations
- Familiarizing with the Destinations UI
- Databases
-
Data Warehouses
- Amazon Redshift
- Databricks
- Firebolt
- Hevo Managed Google BigQuery
- Google BigQuery
- Snowflake
-
Destination FAQs
- Can I create a Destination through API?
- 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?
- Transform
- Alerts
- Account Management
- Personal Settings
- Team Settings
-
Billing
- Pricing Plans
- Time-based Events Buffer
- Setting up Pricing Plans, Billing, and Payments
- On-Demand Purchases
- Billing Alerts
- Viewing Billing History
- Billing Notifications
-
Billing FAQs
- Can I try Hevo for free?
- 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?
- When will I be charged for my subscription?
- 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?
- What is a free Source?
- 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?
- What are the payment methods available in Hevo?
- Can you explain the pricing plans in Hevo?
- Where do I get invoices for payments?
- Is my billing information removed upon account deletion?
- Account Suspension and Restoration
- Account Management FAQs
- Activate
- Glossary
- Release Notes
- 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
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.
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-Only
privileges or provide all Access-API privileges. -
Click PIPELINES in the Asset Palette.
-
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.
Example: https://469-HOO-201.mktorest.com/rest
-
Identity Endpoint - The endpoint used to retrieve access tokens using the Client ID and Client Secret.
Example: https://469-HOO-201.mktorest.com/identity
-
-
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.
Data Replication
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:
Data Model
The following is the list of tables (objects) and their primary keys that are created at the Destination when you run the Pipeline.
If you have selected AutoMapping, Hevo creates the tables in the Destination automatically. Else, you must manually create and map the tables. See sample image here:
Note: The table names are written in small case, except for the Snowflake data warehouse tables which are written in uppercase.
Table | Primary Key | Parent Object | Bulk API |
---|---|---|---|
activity_types (Custom activity types as well as Marketo-provided activity types are loaded into the same table.) |
ID | NA | NA |
campaigns | ID | NA | NA |
lead_activities | marketoGUID | NA | Bulk activity extract |
leads | leadId | NA | Bulk lead extract |
opportunity | marketoGUID | lead_activities | NA |
oppportunity_role | marketoGUID | lead_activities | NA |
program | ID | NA | NA |
program_members | ID | program | Bulk program member extract |
sales_persons | ID | lead_activities | NA |
smart_list | ID | campaigns | NA |
Linked objects: Wherever there is a dependency between objects, the job is created for only the higher-level object. The same job fetches the data for the linked object also. However, you can see separate tables in Schema Mapper for each such linked object. For example, when you fetch Campaigns data, Smart List data is automatically fetched. So, while you see the Smart List table in Schema Mapper, there is no job created by this name.
Additional Information
Read the detailed Hevo documentation for the following related topics:
Revision History
Refer to the following table for the list of key updates made to this page:
Date | Release | Description of Change |
---|---|---|
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. |