From Oracle to BigQuery using AWS S3

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 s3_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 bigquery_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 - Amazon Simple Storage Service

AWS S3 is the industry-leading object storage service. LakeXpress stages Parquet files in S3 for scalable, durable, and cost-effective cloud storage before publishing to your target platform.

Features:

•Unlimited scalability
•99.999999999% durability
•Lifecycle policies for cost optimization
•Server-side encryption
•Integration with AWS Glue Data Catalog

Destination - BigQuery

Google BigQuery is a serverless, highly scalable data warehouse. LakeXpress loads Parquet files from GCS into BigQuery tables using native bulk loading.

Publishing method:

BigQuery Load Job from GCS

Features:

•Direct load from GCS
•Native Parquet format support
•Automatic schema detection
•Petabyte-scale analytics
•Integration with Google Cloud ecosystem

Related Pipelines

Oracle → ABS → MotherDuck

Oracle → ABS → Databricks

Oracle → ADLS → Snowflake

MySQL → S3 → BigQuery

SAP HANA → S3 → DuckLake

Oracle → S3 → MotherDuck