From Teradata to BigQuery using Azure Blob 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_teradata_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 abs_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 - Teradata

Teradata is an enterprise-class data warehousing and analytics platform. LakeXpress uses FastBCP with optimized Teradata connectors for efficient data extraction to Parquet format.

Features:

•Native Teradata .NET driver via FastBCP
•Full support for Teradata-specific types
•Parallel extraction to Parquet files
•Optimized for large-scale data warehouses

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 - Azure Blob Storage

Azure Blob Storage is Microsoft's object storage solution for the cloud. LakeXpress uses Azure Blob as an intermediate staging layer for Parquet files with high performance and reliability.

Features:

•Massive scalability
•Multiple access tiers (Hot, Cool, Archive)
•Integrated with Azure ecosystem
•Built-in encryption and security
•Lifecycle management policies

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

Teradata → ADLS → AWS Glue

Teradata → ADLS → DuckLake

Teradata → ABS → Fabric

Teradata → S3 → DuckLake

Teradata → ABS → Redshift

SQL Server → ABS → BigQuery