Understanding your Monthly Active Rows (MARs) usage in Windsor.ai

Windsor.ai has a SaaS pricing model with fixed plans, including a limited data volume per plan for database destinations, measured in Monthly Active Rows (MARs).

While Windsor.ai doesn’t charge directly per MAR usage, each plan includes a fixed MAR allowance. If your usage exceeds that amount, you can either:

• Pay for the additional MARs at your plan’s rate at the end of the billing cycle, or
• Upgrade your plan for greater included volume 

MARs tracking gives you a clear view of how much data your pipelines process and helps optimize sync frequency, filtering, and source configuration.

Monthly Active Rows represent the number of unique rows or data records processed and streamed to your data warehouse or database destination within a given billing period. It’s a measure of how many distinct data records were actually written or updated during the month.

MARs don’t count the number of transformations or repeated queries, only the unique rows inserted or updated in the destination.

For instance, if 10,000 unique campaign-day rows were loaded to BigQuery during the billing cycle, your Monthly Active Rows = 10,000.

In Windsor.ai, we follow a typical approach to measuring MARs based on the total volume of unique rows transferred or updated in data warehouse destinations during a billing month:

• A unique row means a new record transferred into a supported destination.
• Data updates and overwrites also contribute to MARs, since they involve transferring new unique rows to the destination.
• MARs are reset monthly at the start of each billing cycle. 
• For backfills, if there were no updates and the same set of fields is used, we don’t count MARs.

How it works: Each record your connector returns is hashed, and these unique hashes are used to determine how many distinct rows have been synced.

If a row’s data values change, its hash changes as well, so it’s counted as a new active row. If a row’s data stays identical across syncs, Windsor.ai recognizes it as unchanged and does not count it again.

This ensures you are measured only on new or updated data, not repeated syncs of the same data.

Let’s look at a simple example to understand how Windsor.ai counts Monthly Active Rows. 

Suppose you have a small campaign performance table with spend and clicks:

Week 1: Initial sync

All three records are new, so 3 MARs are counted.

Week 2: Updates

If the spend for campaign b was updated from 200 to 250:

• That row’s hash changes.
• Windsor.ai counts it as a new MAR because the data for the spend field changed.

Now the total is 4 MARs for this billing month.

Week 3: No data changes

If you re-sync the same data with identical values, no new MARs are counted.

Week 4: Add new campaign

Adding a new campaign d means one new data point inserted results in +1 MAR. The total MARs this month are 5.

You can pay for the additional used MARs at the end of the billing period without changing your plan, or upgrade when your data usage consistently exceeds your allowance.

You can track MAR usage inside your Windsor.ai dashboard. Go to your windsor account. Find Settings → Manage account and click on it. Here you can see your current MARs usage.

Example 1: New rows added (increases MARs)

Example 2: Updating existing records (increases MARs)

Example 3: Re-sync or backfill (doesn’t increase MARs)

Example 4: Syncing to a BI tool (no MAR impact)

Example 5: Large historical import (rapid MAR increase)

Historical imports are often the biggest contributors to MAR spikes. Schedule them wisely.

Example 6: How MARs grow over time

Notes:

• If Week 3 contained only re-synced unchanged data: total stays 150K.
• If the 1M backfill includes previously synced rows with no changes: the final total would be lower than 1.16M, since duplicates and unchanged data aren’t counted again.
• If your plan includes 1M MARs and your final count reaches 1.16M, you will exceed 160K MARs. The additional usage will be billed at your plan’s extra MAR rate as outlined on windsor.ai/pricing.

Windsor.ai’s Monthly Active Rows (MARs) metric provides a transparent and efficient way to understand how much data your pipelines move every month.

By tracking unique data hashes, Windsor accurately measures only new or changed records, ensuring that unchanged or duplicate syncs never inflate your usage.

This approach gives you a fair and realistic view of your actual data activity, while Windsor’s plan-based pricing keeps your costs predictable and transparent.

Whether you are syncing marketing data into BigQuery, pushing CRM data into Looker Studio or automating dashboards across multiple destinations, your MAR usage reflects genuine data movement, not redundant re-syncs.