From Hubspot to SQL Server: managed, scheduled, no code.
Creating a pipeline that sends data from Hubspot to SQL Server databases takes only a few minutes with Kondado. And the whole integration from Hubspot to SQL Server is managed and executed by our platform. With Kondado, you can focus on extracting value from Hubspot data and combining it with other data in your SQL Server database
You can replicate your marketing, sales, and service data from Hubspot to SQL Server using Kondado’s automated pipelines. The platform connects directly to your Hubspot account and transfers data to your SQL Server database on a configurable schedule without requiring any coding or technical setup. This allows you to centralize your CRM data alongside other business information for comprehensive analysis and reporting.
Kondado provides direct integration between Hubspot and SQL Server, replicating data from 24 available pipelines including Companies, Contacts, Deals, and Email Events on a configurable schedule ranging from every 5 minutes to daily. The platform handles the data transfer automatically, maintaining updated records in your SQL Server database so you can build custom reports and analyze your marketing and sales performance using your preferred business intelligence tools.
Once your data lands in SQL Server, you can combine Hubspot Contacts and Deals pipelines with financial records to calculate customer lifetime value and sales conversion rates by campaign source. Analyze Email Events data alongside website analytics to measure engagement trends and optimize your inbound marketing strategies. With 805 fields available across 24 pipelines, you can create comprehensive SQL queries that join customer service tickets with sales history to identify churn risks and upsell opportunities.
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Replicated to SQL Server
Hubspot data available for SQL Server
Tables Kondado writes into your SQL Server, on a schedule you control.
24
available pipelines
805
extractable fields
SQL Server
Destination
Available integrations
Companies
Includes information such as id, name, and properties related to contacts and deals.
Contact lists
Presents contact lists with details on membership and relevant properties.
Contacts
Brings contact information such as id, email, name, and created date.
Contacts: form submissions
Includes form submissions with fields such as conversion id, content type, and form id.
Contacts: lists membership
Displays the association of contacts to specific lists and their properties.
Custom object
Represents custom objects with fields such as id and specific properties.
Deals
Contains information about deals, including id, value, and related contacts.
Email events
Records email events with details on sending, opens, and clicks.
Engagements: Calls
Includes call details such as id, dispositions, and related objects.
Engagements: Emails
Presents email details including id and related objects.
Engagements: Meetings
This table contains information about meetings, including fields such as id, contact_id, company_id, and updated_at.
Engagements: Notes
Notes table includes fields such as id, contact_id, body, and created_at, allowing tracking of relevant information.
Engagements: Tasks
Tasks table presents fields such as id, contact_id, due_date, and status, facilitating activity management.
Feedback Submissions
Feedback submissions table includes fields such as id, contact_id, feedback_type, and created_at, allowing analysis of responses.
Leads
Leads table contains information such as id, email, status, and created_at, essential for managing potential customers.
Line Items
Line items table presents fields such as id, deal_id, product_id, and quantity, useful for tracking sales.
Marketing Emails
Marketing emails table includes fields such as id, subject, sent_date, and open_rate, allowing analysis of campaigns.
Owners
Owners table contains fields such as id, name, email, and created_at, essential for user management.
Payments
Payments table includes fields such as id, amount, payment_date, and status, useful for financial control.
Pipelines
Pipelines table presents fields such as id, name, stage, and created_at, important for sales management.
Products
Table contains information about products, including fields such as id, name, price, and description.
Properties Metadata
Table presents metadata of properties, including fields such as name, type, and description.
Property History
Table logs changes to properties, with fields such as id, created_at, and previous_value.
Tickets
Table includes information about tickets, with fields such as id, status, priority, and created_at.
Sync data automatically — no code, no manual exports.
1
Connect Your Hubspot Account
Authenticate your Hubspot portal using OAuth credentials to establish the data source connection. Kondado will automatically detect available pipelines and field structures from your CRM.
2
Configure SQL Server Destination
Enter your SQL Server connection details including server address, database name, and credentials to establish the target location. You can specify custom schemas or table prefixes to organize your replicated data.
3
Select Pipelines and Schedule
Choose which of the 24 available pipelines to enable and set your preferred update frequency from every 5 minutes to daily. Kondado will begin replicating data immediately according to your configuration.
Try out all the features for free for 14 days
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Why Kondado?
Focus on extracting value from your data and leave the rest to us
Answers about sending Hubspot data to SQL Server automatically
How does Kondado replicate Hubspot data to SQL Server without coding?▼
Kondado uses OAuth authentication to connect directly to your Hubspot account and automatically structures the data for SQL Server ingestion. You simply authorize the connection, select your desired pipelines, and configure the sync schedule through the visual interface.
Which Hubspot objects can I replicate to SQL Server?▼
You can replicate 24 different pipelines including Contacts, Companies, Deals, Tickets, Marketing Emails, and custom objects. Each pipeline contains specific fields such as contact properties, deal values, email open rates, and engagement history that land as structured tables in your database.
How often does Kondado update my Hubspot data in SQL Server?▼
You can configure automated updates to run every 5 minutes, 15 minutes, hourly, or daily depending on your business requirements. The schedule runs continuously once set, ensuring your SQL Server database reflects the latest changes from your CRM without manual intervention.
What format does Hubspot data take when it arrives in SQL Server?▼
Data arrives as relational tables with properly typed columns matching Hubspot's API field structures, including timestamps, text fields, and numeric values. You can query this data directly using T-SQL or connect business intelligence tools like Power BI to build visualizations.
Can I combine Hubspot data with other sources in my SQL Server database?▼
Yes, you can replicate data from additional sources alongside Hubspot into the same SQL Server instance. This allows you to write SQL joins between your CRM records and data from PostgreSQL or other databases for unified reporting.
Do I need to map fields manually when sending Hubspot data to SQL Server?▼
Kondado automatically maps all 805 available fields from Hubspot's API to corresponding SQL Server columns during the initial setup. You can select which specific pipelines to enable or disable, but the field structure and data types are handled automatically by the platform.
Can I send Hubspot data from multiple portals to the same SQL Server database?▼
You can configure separate connections for different Hubspot portals within your Kondado account, each writing to distinct schemas or table prefixes in your SQL Server database. This setup allows agencies and large enterprises to consolidate data from multiple clients or business units into a single analytical environment.
How do I analyze Hubspot data once it is in SQL Server?▼
You can query the replicated tables directly using SQL Server Management Studio or connect visualization tools like Looker Studio and Power BI to create custom dashboards. Many users also export subsets to Google Sheets for ad-hoc analysis while maintaining the master dataset in SQL Server.
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