From MariaDB to AWS Glue 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_mariadb_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 aws-glue_tgt

# First sync - full load
./LakeXpress sync

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

Documentation

Get LakeXpress

Source - MariaDB

MariaDB is a MySQL fork offering advanced features and better performance. LakeXpress ensures full compatibility with MariaDB through FastBCP.

Features:

•Full MySQL compatibility
•Support for advanced MariaDB features
•Optimized extraction performance
•Parallel processing to Parquet

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 - AWS Glue

AWS Glue is a serverless data integration service. LakeXpress publishes Parquet files to S3 and registers tables in the Glue Data Catalog for seamless query access.

Publishing method:

S3 + Glue Catalog Table Registration

Features:

•Automatic schema registry in Glue Catalog
•Integration with Athena for SQL queries
•Crawlers for metadata discovery
•Partition management
•EMR and Redshift Spectrum compatibility

Related Pipelines

MariaDB → S3 → MotherDuck

PostgreSQL → S3 → AWS Glue

PostgreSQL → ABS → DuckLake

MariaDB → S3 → Snowflake

PostgreSQL → ABS → Fabric

Oracle → GCS → AWS Glue