Understanding the Sync Frequencies in the Database Destination

Learn the different sync frequency options available for Dataslayer’s Database destination: Scheduled, Manual, and Manually Split, and when to use each.

When you export marketing or analytics data from Dataslayer into a Database (for example, a data warehouse or any SQL/managed database), choosing the right sync frequency affects freshness, reliability, and cost.

Below we describe each option and give practical recommendations so you can pick the best workflow for your use case.

Scheduled Syncs 

The Scheduled Sync runs automatically on a cadence you configure (daily, weekly, etc.), pushing new or updated data into your database without manual steps.

Use this when you want an always-updated dataset available to BI tools, reporting dashboards, or downstream pipelines. Once set up, Dataslayer handles the routine synchronization so your database reflects the latest marketing metrics.

Best for

• Regular, recurring exports (daily/weekly)

• Keeping dashboards and BI sources up to date

• Routine pipelines and automated reporting

When to choose it

• You need predictable, hands-off updates

• You want to avoid manual triggering every time

Manual Sync 

The Manual Sync lets you trigger a one-off export whenever you need it. All selected data is written to your database in a single run.

This is ideal for testing, ad-hoc analyses, or when you only occasionally need to move data.

Best for

• One-time exports (e.g., last month’s report)

• Validating connection or schema during setup

• Small datasets or exploratory pulls

When to choose it

• You want maximum control over timing

• You’re iterating on queries or troubleshooting

Manually Split Sync 

For very large queries: multi-year history, many accounts, or very granular daily metrics. The Manually Split Sync prevents timeouts and failures by splitting the export into smaller, sequential chunks.

This option divides the overall query (usually by time slices) and performs multiple uploads in sequence. Because it processes the data in parts, it’s more robust for heavy transfers but can take longer to finish.

Best for

• Multi-year historical dumps

• Accounts with highly granular daily metrics

• Avoiding failures on large exports

As always, please contact us via our live chat on our website or via email if you still have doubts or questions. We are happy to help!