Amazon DynamoDB to Google BigQuery Integration
AI-first ETL from Amazon DynamoDB into Google BigQuery. Governed entities, incremental sync, typed landing tables.
How Datrise loads Amazon DynamoDB into Google BigQuery
Datrise syncs Amazon DynamoDB's tables, items, partition keys, sort keys, attributes, and stream records into Google BigQuery as a partitioned table per source entity. Flexible or custom fields land in JSON or nested/repeated (STRUCT) columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.
Sync is incremental: Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target, so re-runs update only what changed. Partition by ingestion or event date and cluster by entity id to keep scanned bytes low. BigQuery bills by bytes scanned, so Datrise partitions and clusters every table to keep query costs predictable.
Ideal for Google-stack analytics and ML on serverless infrastructure.
Endpoints
Amazon DynamoDB: Serverless key-value and document store on AWS.
Google BigQuery: Serverless analytics warehouse on GCP.
How Amazon DynamoDB entities map to Google BigQuery
| Amazon DynamoDB entity | Google BigQuery object | Notes |
|---|---|---|
| tables | source_dynamodb_tables | id PK · custom fields → JSON or nested/repeated (STRUCT) columns |
| items | source_dynamodb_items | id PK · linked to source_dynamodb_tables |
| partition keys | source_dynamodb_partition_keys | id PK · linked to source_dynamodb_tables |
| sort keys | source_dynamodb_sort_keys | id PK · linked to source_dynamodb_tables |
FAQ
How does Datrise handle Amazon DynamoDB's custom fields in Google BigQuery?
Flexible values are stored as JSON or nested/repeated (STRUCT) columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Google BigQuery types.
How does the Amazon DynamoDB to Google BigQuery sync stay up to date?
It runs incrementally — Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target.
Related pipelines
More destinations for Amazon DynamoDB
- Amazon DynamoDB → Amazon Redshift
- Amazon DynamoDB → Databricks SQL Warehouse
- Amazon DynamoDB → ClickHouse
- Amazon DynamoDB → DuckDB
- Amazon DynamoDB → Amazon Athena
- Amazon DynamoDB → Amazon S3 Data Lake
- Amazon DynamoDB → Azure Data Lake Storage
- Amazon DynamoDB → Azure Synapse
- Amazon DynamoDB → Spreadsheets
- Amazon DynamoDB → Airtable
- Amazon DynamoDB → CSV Files
- Amazon DynamoDB → MongoDB
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Early access
Connect Amazon DynamoDB to Google BigQuery the easy way
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