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Connect Chartmogul to MySQL

Connect Chartmogul to MySQL and export selected accounts, metrics, and dimensions to your MySQL project.

Configure the historical window, destination table, and recurring schedule without maintaining a Chartmogul API pipeline.

Used by the world's leading companies

Export Chartmogul data to MySQL

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Chartmogul data in MySQL

Bring all your Chartmogul data into your warehouse and make it available for analytics, machine learning, and internal applications.

Data freshness

Keep your MySQL tables up to date

Automatically sync new data from Chartmogul so every dashboard, model, and report works with fresh information.

Analysis

Unify Chartmogul with the rest of your business data

Join marketing, finance, CRM, and product data inside the same warehouse.

Chartmogul metrics and dimensions available in MySQL

Access 11 metrics and 40 dimensions from Chartmogul connectors including MRR, ARR, ARPA, Customer Churn Rate, MRR Churn Rate, LTV, Date, Customer Company, Customer Status, Customer Country, Customer Currency and many more...

11

Metrics availables

40

Dimensions availables

Connect Chartmogul to MySQL in minutes

Move your data from Chartmogul to MySQL with a simple setup. Once connected, Catchr handles the ingestion automatically so your warehouse stays up to date without manual work.

Step one

Connect your Chartmogul account

Authenticate your Chartmogul account securely in Catchr. No custom scripts, API maintenance, or engineering work required.

Client A · Connected sources
5 sources ready
Chartmogul 3 advertising accounts Connected
Google Ads 2 advertising accounts Connected
Google Analytics 4 1 web property Connected
HubSpot 1 CRM portal Connected
Step two

Choose the MySQL destination

Connect your existing MySQL database with its host, port, username, password, and database name. Then create the datastream that defines where the selected source data should go.

Destination / MySQL Required fields
Host Required
analytics-db.internal
Username Required
catchr_writer
Password Required
••••••••••••
Database Required
marketing_reporting
Step three

Keep your MySQL tables updated

Choose the fields, initial history, partition field, and recurring schedule for the job. Catchr refreshes the configured import window in your MySQL table.

Export job / MySQL Example
Database Destination
marketing_reporting
Table Per job
google_ads_campaigns
Recurring schedule Choose a cadence
Every 6 hours
Daily · 06:00
Weekly · Mon
Export readySelected fields · configured history
Every 6 hours

Review 30-day Chartmogul subscription revenue in SQL.

This example summarizes recurring revenue, active customers, churned customers, and churn rate by plan.

Chartmogul.sql
BigQuery SQL
30-day window
SELECT
  plan_name,
  SUM(mrr) AS mrr,
  SUM(active_customers) AS active_customers,
  SUM(churned_customers) AS churned_customers,
  SAFE_DIVIDE(
    SUM(churned_customers),
    SUM(active_customers)
  ) AS churn_rate
FROM `your_project.marketing_raw.chartmogul_subscriptions_daily`
WHERE date >= DATE_SUB(
  CURRENT_DATE(),
  INTERVAL 30 DAY
)
GROUP BY plan_name
ORDER BY mrr DESC;
Illustrative SQL — adapt it to the fields and schema selected in your export. Standard SQL

Connect more table to your Chartmogul data

Open the dedicated route for each platform. Its field catalog, reporting grain, historical constraints, and warehouse use cases should be specific to that source.

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Before you schedule the job.

Answers about MySQL setup, available source data, schedules, table updates, and SQL use cases.

What is the setup for sending Chartmogul data to MySQL?

Add Chartmogul in Sources and connect the existing MySQL database in Storage. A datastream defines the route, while the job loads the chosen fields into "subscriptions".

What can I select from Chartmogul before writing to MySQL?

Select concrete Chartmogul fields such as ARPA, ARR, ASP, and Day of the month. You can rename the chosen columns, preview the result, and write them to MySQL tables such as customers, subscriptions, and plans.

Can a Chartmogul-to-MySQL job import historical periods?

Define the first Chartmogul fetch, run frequency, and lookback window in the "subscriptions" job. Each scheduled run replaces data inside the configured period.

Why does the Chartmogul MySQL job need a partition field?

Use a supported date field to partition "subscriptions". Recurring Chartmogul runs can then update the selected window instead of adding another copy of the same period.

Which decisions can a Chartmogul MySQL dataset support?

With Chartmogul data, a MySQL query can summarize recurring revenue, active customers, churned customers, and churn rate by plan. Model ARPA and ARR in SQL, then expose the result to dashboards, internal tools, or recurring client reports.

Does my MySQL database need to exist before I connect it?

Yes. Connect an existing MySQL database first. The Catchr job creates and populates the destination table you configure inside that database.

Can I load several marketing sources into the same MySQL database?

Yes. Create a separate datastream and job for each source, write each export to its own table, then combine the data downstream with SQL, views, or your BI tool.

Still have a question ? 

Our teams is always here to responds to any question you could have about our data connector. 

Your next MySQL reporting table should not start with five exports.

Connect your accounts, choose the fields, then schedule the data your team needs in MySQL.

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