How does Kondado replicate Stilingue data to MySQL?

Kondado connects directly to the Stilingue API as a data source and writes structured sentiment data into your MySQL database. The platform extracts metrics from five different analysis pipelines including term, hashtag, and theme sentiment, then loads them on your configured schedule without requiring manual CSV exports or custom scripts.

What Stilingue sentiment metrics are available in MySQL?

You can access 139 fields across five pipelines including total polarity counts, positive classifications, negative sentiment volumes, and neutral mentions. Specific pipelines like Sentiment by Terms and Sentiment by Groups provide detailed breakdowns of how audiences perceive specific keywords, tags, or categorized content segments.

How often does Stilingue data update in MySQL?

Kondado updates your MySQL database on a configurable schedule that you set during setup, with options ranging from every 5 minutes to daily intervals. This ensures your social listening metrics reflect recent conversations without overwhelming your database with constant writes.

Can I combine Stilingue data with other sources in MySQL?

Yes, once Stilingue data resides in MySQL, you can join it with information from BigQuery , PostgreSQL , or other supported platforms that also write to your database. This allows you to create unified reports correlating social sentiment with sales figures, advertising spend, or customer service data.

What format does Stilingue data take in MySQL?

Data arrives as structured relational tables with standardized column names for sentiment classifications, counts, and metadata fields. Each pipeline creates distinct datasets that include metrics like total_polarity_classified alongside positive, negative, and neutral sentiment tallies ready for SQL analysis.

Do I need technical skills to set up Stilingue to MySQL replication?

No coding is required to establish the connection, as Kondado provides a guided interface for authenticating your Stilingue account and configuring your MySQL destination. The platform handles API authentication, data type mapping, and schema creation automatically while you simply select which sentiment pipelines to include.

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Send Stilingue Data to MySQL Automatically

Connecting Stilingue to MySQL requires no coding or complex configuration. Simply authenticate your Stilingue account as a data source, configure your MySQL database as the destination, and select which sentiment pipelines you want to replicate. Kondado handles the data extraction, formatting, and loading automatically on your chosen schedule, whether every 5 minutes, hourly, or daily. This automated pipeline ensures your social listening metrics stay current in your database without manual exports or spreadsheet maintenance.

Kondado replicates Stilingue social listening data to MySQL automatically on a configurable schedule, making 139 fields from 5 sentiment analysis pipelines available for SQL querying and custom reporting.

Once your data arrives in MySQL, you can join Stilingue sentiment metrics with CRM records, advertising data, or sales figures to uncover correlations between brand perception and business outcomes. Analysts can build custom dashboards in Power BI, Looker Studio, or Google Sheets by querying their MySQL database directly, creating comprehensive reports that combine social sentiment with operational data.

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The Sentiment by Terms pipeline delivers granular polarity metrics for specific keywords, enabling you to track brand health campaigns or product mentions with precise SQL filters and time-series analysis. With Sentiment by Hashtags, marketing teams can measure campaign effectiveness by analyzing positive and negative associations across tracked tags directly in their MySQL environment. These datasets become significantly more powerful when combined with other business data, allowing you to correlate sentiment trends from Sentiment by Themes with web traffic, conversion rates, or customer support tickets stored in the same database for holistic performance analysis.

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Stilingue data available for MySQL

available pipelines

139

extractable fields

Available integrations

Integration	Description
Sentiment by Terms	Analyzes sentiment towards specific terms, presenting metrics such as total, positive, negative, and neutral, along with total_polarity_classified.
Sentiment by Themes	Evaluates sentiment towards themes, including metrics such as total, positive, negative, and neutral, along with total_polarity_classified.
Sentiment by Hashtags	Examines sentiment associated with hashtags, featuring metrics such as total, positive, negative, and neutral, along with total_polarity_classified.
Sentiment by Tags	Investigates sentiment towards tags, presenting metrics such as total, positive, negative, and neutral, along with total_polarity_classified.
Sentiment by Groups	Analyzes sentiment towards groups, with metrics such as total, positive, negative, and neutral, along with total_polarity_classified.

Sentiment by Terms

Analyzes sentiment towards specific terms, presenting metrics such as total, positive, negative, and neutral, along with total_polarity_classified.

Sentiment by Themes

Evaluates sentiment towards themes, including metrics such as total, positive, negative, and neutral, along with total_polarity_classified.

Sentiment by Hashtags

Examines sentiment associated with hashtags, featuring metrics such as total, positive, negative, and neutral, along with total_polarity_classified.

Sentiment by Tags

Investigates sentiment towards tags, presenting metrics such as total, positive, negative, and neutral, along with total_polarity_classified.

Sentiment by Groups

Analyzes sentiment towards groups, with metrics such as total, positive, negative, and neutral, along with total_polarity_classified.

See all available data →

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How to send Stilingue data to MySQL

Sync data automatically — no code, no manual exports.

Connect Stilingue Account

Authenticate your Stilingue credentials in Kondado to establish the data source and enable access to sentiment analysis pipelines.

Configure MySQL Destination

Enter your MySQL connection details including host, port, database name, and credentials to establish where your Stilingue data will be written.

Select Pipelines and Schedule

Select your desired sentiment pipelines from the five available options and configure the update schedule to match your reporting needs. Once in MySQL, you can visualize this data in Power BI, Looker Studio, or Google Sheets by connecting directly to your database.

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