Apache Spark → Amazon Redshift
AI-first ETL from Apache Spark into Amazon Redshift. Governed entities, incremental sync, typed landing tables.
How Datrise loads Apache Spark into Amazon Redshift
Datrise syncs Apache Spark's records, events, and configuration objects into Amazon Redshift as a typed table per source entity. Flexible or custom fields land in SUPER columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMPTZ.
Sync is incremental: Datrise uses COPY from staged files, then a delete-and-insert merge on stable id, so re-runs update only what changed. A DISTKEY on the join id and a SORTKEY on the load timestamp. Redshift performance hinges on dist/sort keys, so Datrise picks them from your entity ids and sync timestamps rather than defaulting to EVEN distribution.
Ideal for AWS-native warehouses already using the Redshift ecosystem.
Endpoints
Apache Spark: SaaS or API data source for analytics and warehouse sync.
Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.
How Apache Spark entities map to Amazon Redshift
| Apache Spark entity | Amazon Redshift object | Notes |
|---|---|---|
| records | apache_spark_records | id PK · custom fields → SUPER columns |
| events | apache_spark_events | TIMESTAMPTZ events |
| configuration objects | apache_spark_configuration_objects | id PK · linked to apache_spark_records |
FAQ
How does Datrise handle Apache Spark's custom fields in Amazon Redshift?
Flexible values are stored as SUPER columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon Redshift types.
How does the Apache Spark to Amazon Redshift sync stay up to date?
It runs incrementally — Datrise uses COPY from staged files, then a delete-and-insert merge on stable id.
Related pipelines
More destinations for Apache Spark
- Apache Spark → Databricks SQL Warehouse
- Apache Spark → ClickHouse
- Apache Spark → DuckDB
- Apache Spark → Amazon Athena
- Apache Spark → Amazon S3 Data Lake
- Apache Spark → Azure Data Lake Storage
- Apache Spark → Azure Synapse
- Apache Spark → Spreadsheets
- Apache Spark → Airtable
- Apache Spark → CSV Files
- Apache Spark → MongoDB
- Apache Spark → Supabase
More sources for Amazon Redshift
- Apify → Amazon Redshift
- Appfollow → Amazon Redshift
- Apple Search Ads → Amazon Redshift
- Ashby → Amazon Redshift
- Autopilot → Amazon Redshift
- Autopilot Activities → Amazon Redshift
- Aws Cloudtrail → Amazon Redshift
- Azure Table Storage → Amazon Redshift
- Azureblobstorage → Amazon Redshift
- Babelforce → Amazon Redshift
- Bigcommerce → Amazon Redshift
- Bigquery → Amazon Redshift
Early access
Connect Apache Spark to Amazon Redshift the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.