From Oracle to Snowflake using Google Cloud Storage

Configure your LakeXpress data pipeline with the selected components

LakeXpress Orchestrator

Manages end-to-end pipelines
Orchestrates FastBCP extracts with retries & logging
Handles incremental sync and schema-aware metadata

Control DB for increments/custom rules & logsMetadata-drivenLinux or Windows

Data

FastBCPEngine

Parquet

Data or Link

Terminal

./LakeXpress config create \
  -a data/ds_credentials.json \
  --log_db_auth_id log_db_ms \
  --source_db_auth_id datasource_oracle_01 \
  --source_db_name sales \
  --source_schema_name "sales,dim" \
  --fastbcp_dir_path ./FastBCP_linux-x64/latest/ \
  --fastbcp_p 2 \
  --n_jobs 4 \
  --target_storage_id gcs_lake_prd \
  --generate_metadata \
  --sub_path /ingest/bronze \
  --incremental_table "sales.orders:o_orderdate:date" \
  --incremental_table "sales.lineitem:l_shipdate:date" \
  --publish_method internal \
  --publish_target snowflake_tgt

# First sync - full load
./LakeXpress sync

# Subsequent syncs - incremental updates (much faster!)
./LakeXpress sync

Documentation

Get LakeXpress

Source - Oracle Database

Oracle Database is the world's most widely used enterprise database. LakeXpress uses FastBCP with optimized Oracle connectors for high-performance data extraction to Parquet format.

Features:

•Native Oracle ODP.NET driver via FastBCP
•Full support for Oracle-specific types
•Parallel extraction to Parquet files
•Optimized for large volumes

Format - Apache Parquet

Parquet is the industry-standard columnar file format for analytics. LakeXpress uses FastBCP to extract data from source databases and convert it to Parquet format, ensuring optimal compression, query performance, and compatibility with all modern data platforms.

Advantages:

•Columnar format optimized for analytics
•Efficient compression (typically 3-10x)
•Schema evolution support
•Predicate pushdown for fast queries
•Universal compatibility with cloud platforms
•Preserves data types and precision

Cloud Stage - Google Cloud Storage

Google Cloud Storage offers unified object storage for developers and enterprises. LakeXpress stages Parquet files in GCS for seamless integration with Google Cloud data platforms.

Features:

•Global edge caching
•Multiple storage classes
•Strong consistency
•Integrated with BigQuery
•Automatic encryption at rest

Destination - Snowflake

Snowflake is a cloud data platform built for analytics. LakeXpress publishes Parquet files from cloud storage directly into Snowflake using COPY INTO commands for optimal performance.

Publishing method:

COPY INTO with MATCH_BY_COLUMN_NAME

Features:

•Direct COPY FROM stage (S3, Azure, GCS)
•Automatic schema detection from Parquet
•Zero-copy cloning capabilities
•Automatic clustering and optimization
•Support for semi-structured data

Related Pipelines

SQL Server → ABS → Snowflake

SAP HANA → GCS → Snowflake

SQL Server → GCS → Snowflake

Oracle → S3 → MotherDuck

MySQL → GCS → AWS Glue

Oracle → ADLS → Redshift