From SAP HANA to Databricks 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_sap-hana_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 databricks_tgt

# First sync - full load
./LakeXpress sync

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

Documentation

Get LakeXpress

Source - SAP HANA

SAP HANA is a high-performance in-memory database platform. LakeXpress optimizes extractions from HANA using FastBCP to leverage its in-memory capabilities.

Features:

•Native SAP HANA connector via FastBCP
•Support for views and columnar tables
•Optimized for in-memory data
•High-speed parallel extraction

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 - Databricks

Databricks provides a unified analytics platform built on Apache Spark. LakeXpress publishes Parquet files as Delta Lake tables for optimal lakehouse performance.

Publishing method:

Delta Lake MERGE or COPY INTO

Features:

•Native Parquet and Delta Lake support
•ACID transactions
•Time travel and versioning
•Optimized for analytical queries
•Unity Catalog integration

Related Pipelines

SAP HANA → GCS → MotherDuck

SAP HANA → S3 → Fabric

MySQL → S3 → DuckLake

SAP HANA → ADLS → Fabric

Teradata → S3 → MotherDuck

PostgreSQL → S3 → Snowflake