Storage & Warehousing

Databricks

Unified lakehouse platform for data engineering, analytics, and AI

https://www.databricks.com

What It Is

Databricks is a unified data intelligence platform built on Apache Spark that combines data engineering, data science, and business analytics. Its lakehouse architecture merges the best of data warehouses (structured data, ACID transactions, governance) with data lakes (scalability, flexibility, low cost) — powered by Delta Lake. Available on AWS, GCP, and Azure.

How We Use It

We use Databricks for clients who need a unified platform for data engineering and data science. Our work covers lakehouse architecture design, Delta Lake implementation, Unity Catalog setup for governance, PySpark pipeline development, and ML workflow configuration with MLflow. Databricks is our go-to for large-scale processing workloads that benefit from Spark’s distributed computing.

Our Expertise

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Lakehouse Architecture

We design bronze/silver/gold layer architectures with Delta Lake: schema enforcement, time travel, MERGE operations, and automated compaction.
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Unity Catalog

We set up Databricks governance with Unity Catalog: metastore configuration, data access policies, lineage tracking, and cross-workspace data sharing.
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PySpark Development

We build production-grade PySpark applications on Databricks: notebook workflows, library management, cluster configuration, and job scheduling.
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ML & MLflow

We configure ML workflows with MLflow: experiment tracking, model registry, feature engineering pipelines, and model serving endpoints.