DatriseAI-first ETL

Tyntec SMS to Mode Integration

AI-first ETL from Tyntec SMS into Mode. Governed entities, incremental sync, typed landing tables.

How Datrise loads Tyntec SMS into Mode

Datrise syncs Tyntec SMS's SMS messages, recipients, delivery reports, senders, countries, and message costs into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.

Ideal for SQL-first analysis with Python and R notebooks.

Endpoints

Tyntec SMS: Global SMS delivery and message status callbacks.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How Tyntec SMS entities map to Mode

Tyntec SMS entityMode objectNotes
SMS messagestyntec_sms_sms_messagesid PK · custom fields → flattened columns for SQL and notebooks
recipientstyntec_sms_recipientsid PK · linked to tyntec_sms_sms_messages
delivery reportstyntec_sms_delivery_reportsid PK · linked to tyntec_sms_sms_messages
senderstyntec_sms_sendersid PK · linked to tyntec_sms_sms_messages

FAQ

How does Datrise handle Tyntec SMS's custom fields in Mode?

Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.

How does the Tyntec SMS to Mode sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

Early access

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