lakehouse-oss-vs-databricks

Comparing Data Lakehouse implementations: Open Source stack vs Databricks.

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What is a Data Lakehouse?

A Data Lakehouse is a modern data architecture that combines the best of data lakes (low-cost, scalable storage for raw and semi-structured data) and data warehouses (structured, performant, query-optimized storage).
The idea is to provide a single platform that can handle:

• Data ingestion from multiple sources (batch & streaming).
• Storage of structured, semi-structured, and unstructured data.
• ACID transactions on top of the data lake.
• Support for BI, ML, and AI workloads on the same platform.

Open Source Lakehouse

An Open Source Lakehouse uses community-driven projects to build the stack

Databricks Lakehouse

Databricks is a commercial, fully managed lakehouse platform built on top of Delta Lake.

It provides:

• Fully managed storage and compute.
• Delta Lake for ACID transactions.
• Native integration with Spark, MLflow, DBSQL, and Unity Catalog.
• Enterprise-grade security, compliance, and governance. - Optimizations like Photon for query performance.

Pros:

• Simplified management (no need to worry about infrastructure).
• Enterprise support and SLA guarantees.
• Strong ecosystem for ML/AI and advanced analytics.
• Best-in-class performance optimizations.

Cons:

• Vendor lock-in (proprietary extensions).
• Licensing costs.
• Less flexibility to swap components.

Environment Variables Configuration

This project uses environment variables to securely manage all credentials and configurations.

Initial Setup

1. Copy the environment variables example file:

   cp .env.example .env

2. Edit the .env file with your real credentials:

   # Example configuration in .env
   MINIO_ROOT_USER=admin
   MINIO_ROOT_PASSWORD=your_secure_password
   AZURE_STORAGE_ACCOUNT_KEY=your_actual_azure_key
   # ... more configurations

3. Generate the secrets.toml file (you can used the template as well):

   python generate_secrets.py

Execution

Start the full environment using Docker Compose:

docker compose up -d