DatriseAI-first ETL

Excel File to Amazon Athena Integration

AI-first ETL from Excel File into Amazon Athena. Governed entities, incremental sync, typed landing tables.

How Datrise loads Excel File into Amazon Athena

Datrise syncs Excel File's worksheets, rows, columns, headers, cell ranges, and workbooks into Amazon Athena as partitioned Parquet in S3 exposed as an Athena table. Flexible or custom fields land in struct/map columns in Parquet, and timestamps such as created, updated, and status changes are typed as timestamp.

Sync is incremental: Datrise uses writes new Parquet partitions and registers them in the Glue Data Catalog, so re-runs update only what changed. Hive-style partitioning by load date so Athena scans only new data. Athena bills per byte scanned and small files hurt, so Datrise compacts to right-sized Parquet rather than many tiny objects.

Ideal for serverless SQL over an S3 lake without a running warehouse.

Endpoints

Excel File: Spreadsheet workbooks from exports and shared drives.

Amazon Athena: Serverless SQL over S3 data lake tables.

How Excel File entities map to Amazon Athena

Excel File entityAmazon Athena objectNotes
worksheetsexcel_file_worksheetsid PK · custom fields → struct/map columns in Parquet
rowsexcel_file_rowsid PK · linked to excel_file_worksheets
columnsexcel_file_columnsid PK · linked to excel_file_worksheets
headersexcel_file_headersid PK · linked to excel_file_worksheets

FAQ

How does Datrise handle Excel File's custom fields in Amazon Athena?

Flexible values are stored as struct/map columns in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon Athena types.

How does the Excel File to Amazon Athena sync stay up to date?

It runs incrementally — Datrise uses writes new Parquet partitions and registers them in the Glue Data Catalog.

Related pipelines

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