DatriseAI-first ETL

CockroachDB to Amazon S3 Data Lake Integration

AI-first ETL from CockroachDB into Amazon S3 Data Lake. Governed entities, incremental sync, typed landing tables.

How Datrise loads CockroachDB into Amazon S3 Data Lake

Datrise syncs CockroachDB's tables, rows, schemas, secondary indexes, ranges, and change feeds into Amazon S3 Data Lake as columnar Parquet objects partitioned per source entity. Flexible or custom fields land in nested struct/map fields in Parquet, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.

Sync is incremental: Datrise uses writes new date partitions and compacts small files on a schedule, so re-runs update only what changed. Hive-style path partitioning (entity/date) for engine-agnostic reads. A lake has no schema enforcement, so Datrise writes a schema manifest alongside the data to keep downstream engines consistent.

Ideal for an open, engine-neutral storage layer for Spark, Athena, Trino, or DuckDB.

Endpoints

CockroachDB: Distributed SQL with survivable multi-region consistency.

Amazon S3 Data Lake: Object storage landing zone for parquet and snapshots.

How CockroachDB entities map to Amazon S3 Data Lake

CockroachDB entityAmazon S3 Data Lake objectNotes
tablescockroachdb_tablesid PK · custom fields → nested struct/map fields in Parquet
rowscockroachdb_rowsid PK · linked to cockroachdb_tables
schemascockroachdb_schemasid PK · linked to cockroachdb_tables
secondary indexescockroachdb_secondary_indexesid PK · linked to cockroachdb_tables

FAQ

How does Datrise handle CockroachDB's custom fields in Amazon S3 Data Lake?

Flexible values are stored as nested struct/map fields in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon S3 Data Lake types.

How does the CockroachDB to Amazon S3 Data Lake sync stay up to date?

It runs incrementally — Datrise uses writes new date partitions and compacts small files on a schedule.

Related pipelines

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