No-code pipeline · Huggy → SQL Server

Send data from Huggy to SQL Server

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From Huggy to SQL Server: managed, scheduled, no code.

Creating a pipeline that sends data from Huggy to SQL Server databases takes only a few minutes with Kondado. And the whole integration from Huggy to SQL Server is managed and executed by our platform. With Kondado, you can focus on extracting value from Huggy data and combining it with other data in your SQL Server database

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Send Huggy Data to SQL Server Automatically

To send Huggy data to SQL Server, start by adding Huggy as a data source in Kondado using your API credentials. Select SQL Server as your destination and choose which pipelines to replicate from the available options including Agents, Contacts, and Chats. Kondado handles the schema creation and data transfer automatically on your chosen schedule, eliminating the need for manual exports or complex ETL scripts that typically require developer time.

Once configured, your customer communication data flows directly into SQL Server ready for analysis and reporting. You can combine Huggy information with sales data from your CRM or financial records to create comprehensive reports on customer satisfaction trends and individual agent performance metrics. This automated pipeline ensures your database stays current without requiring technical resources to maintain API connections or troubleshoot data sync issues, freeing your team to focus on insights rather than data engineering.

Kondado replicates Huggy’s Agents, Contacts, Chats, and Chat Satisfaction Surveys pipelines directly to SQL Server on a configurable schedule ranging from every 5 minutes to daily, requiring no manual coding or API maintenance.

Our prices start from $19 USD/month, and you can try Kondado for free for 14 days with no credit card required

Available Huggy Pipelines for SQL Server

With the Agents pipeline replicated to SQL Server, you can build performance dashboards tracking response times and workload distribution across your support team. The Contacts and Chats pipelines enable deep analysis of customer interaction histories, allowing you to segment leads based on engagement patterns and identify high-value prospects through SQL queries.

By having this Huggy data available in your SQL Server database, you create a foundation for custom business intelligence that connects customer service metrics with sales performance and marketing campaign results. You can also join Chat Satisfaction Surveys with agent records to correlate service quality with individual team members, driving targeted training initiatives.

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Replicated to SQL Server

Huggy data available for SQL Server

Tables Kondado writes into your SQL Server, on a schedule you control.

available pipelines

extractable fields

SQL Server

Destination

Available integrations

Agents

Table contains information about agents, including fields such as id, name, and department.

Contacts

Table presents contacts with fields such as id, name, phone, and email, enabling efficient lead management.

Chats

Table records chat details, including id, contactid, agentid, and timestamps such as createdat and closedat.

Chat Satisfaction Surveys

Table contains chat feedback, with fields such as chat_id, feedback_score, and feedback_text, allowing satisfaction analysis.

See all available data → Send Huggy to SQL Server →

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How to send Huggy data to SQL Server

Sync data automatically — no code, no manual exports.

Connect Your Huggy Account

Authenticate your Huggy data source in Kondado by entering your API credentials in the connection interface. This establishes the link to your customer communication platform and allows Kondado to access your Agents, Contacts, and Chats data.

Configure SQL Server Destination

Enter your SQL Server connection details including server address, database name, and authentication credentials to establish the destination. Kondado supports various SQL Server versions and will create the necessary schema structure to receive your Huggy pipelines.

Select Pipelines and Schedule

Choose which Huggy pipelines to replicate, such as Contacts for lead management or Chat Satisfaction Surveys for quality analysis, then set your update frequency. You can configure the schedule to run every 5 minutes for near-real-time updates or select longer intervals based on your reporting needs.

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Send data from Huggy to other destinations

Huggy > Looker Studio

Huggy > Power BI

Other visualizations

Huggy > Amazon S3

Huggy > BigQuery

Huggy > Excel

Huggy > Google Sheets

Huggy > MySQL

Huggy > PostgreSQL

Huggy > Redshift

Huggy > SQL Server

Choose a tool to visualize your Huggy data

If the software you need is not listed, drop us a messagem. You can use almost every tool

Huggy > Airtable

Huggy > Alteryx

Huggy > Amazon Quicksight

Huggy > BIMachine

Huggy > Cortex

Huggy > Data Studio

Huggy > Geckoboard

Huggy > Grafana

Huggy > IBM Cognos Analytics

Huggy > Klipfolio

Huggy > Looker Studio

Huggy > Looker

Huggy > Looqbox

Huggy > Metabase

Huggy > Microstrategy

Huggy > Pentaho

Huggy > Power BI

Huggy > Qlik Cloud Analytics

Huggy > Qlik Sense

Huggy > Qlik

Huggy > QlikView

Huggy > Redash

Huggy > Superset

Huggy > Tableau

Huggy > BI TOTVS

Huggy > Zoho Analytics

Frequently Asked Questions (FAQ)

Answers about sending Huggy data to SQL Server automatically

How does Kondado replicate Huggy data to SQL Server? ▼

Kondado connects directly to the Huggy API and your SQL Server database to transfer data automatically. You authenticate both systems once, then select which pipelines to replicate. The platform handles schema mapping and data type conversion, delivering structured data into your SQL Server tables on your configured schedule.

What specific Huggy data can I replicate to SQL Server? ▼

You can replicate four distinct pipelines: Agents with profile details, Contacts with lead information, Chats with conversation records, and Chat Satisfaction Surveys with feedback scores. Each pipeline contains specific fields like agent names, contact emails, chat timestamps, and satisfaction ratings that become available as structured data in your database.

How frequently does Huggy data update in SQL Server? ▼

Update frequency is fully configurable based on your business needs, ranging from every 5 minutes to daily intervals. You set the schedule during pipeline configuration, and Kondado automatically pulls new and updated records from Huggy according to your chosen timeframe.

What format does Huggy data take once in SQL Server? ▼

Each Huggy pipeline becomes a separate table in SQL Server with appropriately typed columns matching the source data structure. Fields like createdat and closedat from Chats arrive as datetime values, while feedback scores store as integers, ready for immediate querying and analysis.

Can I combine Huggy data with other sources in SQL Server? ▼

Yes, once Huggy data resides in SQL Server, you can join it with information from other data sources you have replicated to the same database. You can also send the combined results to Power BI or Looker Studio for visualization, creating unified reports that correlate customer service interactions with sales outcomes.

Which SQL Server versions support Huggy data replication? ▼

Kondado works with standard SQL Server deployments including Express, Standard, and Enterprise editions. The connection uses standard database protocols, making it compatible with SQL Server 2016 through 2022 as well as Azure SQL Database instances.

Do I need technical skills to set up the Huggy SQL Server pipeline? ▼

No coding is required to configure the pipeline between Huggy and SQL Server. The interface guides you through authentication, destination configuration, and pipeline selection without writing SQL or API scripts.

Can I replicate Huggy data to both SQL Server and Power BI simultaneously? ▼

Yes, you can configure multiple pipelines from Huggy to send data to SQL Server and Power BI at the same time. This allows you to maintain a historical database in SQL Server while keeping live dashboards updated in Power BI without writing custom code.

Try out all the features for free for 14 days

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Try out all the features for free for 14 days