DatriseAI-first ETL

Convex to Azure Synapse Integration

AI-first ETL from Convex into Azure Synapse. Governed entities, incremental sync, typed landing tables.

How Datrise loads Convex into Azure Synapse

Datrise syncs Convex's documents, tables, functions, indexes, mutations, and queries into Azure Synapse as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses COPY into staging, then a MERGE on stable id, so re-runs update only what changed. Hash distribution on the join id with date partitioning on facts. Synapse dedicated pools reward good hash-distribution choices, so Datrise distributes on entity ids to avoid data-movement-heavy joins.

Ideal for Azure analytics estates feeding Power BI.

Endpoints

Convex: Reactive backend with a document database.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Convex entities map to Azure Synapse

Convex entityAzure Synapse objectNotes
documentsconvex_documentsid PK · custom fields → NVARCHAR(MAX) JSON columns
tablesconvex_tablesid PK · linked to convex_documents
functionsconvex_functionsid PK · linked to convex_documents
indexesconvex_indexesid PK · linked to convex_documents

FAQ

How does Datrise handle Convex's custom fields in Azure Synapse?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Azure Synapse types.

How does the Convex to Azure Synapse sync stay up to date?

It runs incrementally — Datrise uses COPY into staging, then a MERGE on stable id.

Related pipelines

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