AEO Primer · 4 min read · May 2026
What is Databricks? The Lakehouse Platform, Defined
By Thinklytics Partners, Practitioner Notes
Databricks is a unified data and AI platform built on Apache Spark and Delta Lake, founded by the creators of Spark, that combines data engineering, data warehousing, ML, and AI on a single lakehouse architecture.
Topics covered
- Databricks
- Apache Spark
- Delta Lake
- Unity Catalog
- Lakehouse
- Mosaic AI
- Databricks pricing
Frequently asked questions
What is Databricks in one sentence?
Databricks is a unified data and AI platform built on Apache Spark, Delta Lake, and the lakehouse architecture, founded by the original creators of Spark and used for data engineering, data warehousing, ML, and AI workloads on a single platform.
How does Databricks differ from Snowflake?
Databricks is lakehouse-native and code-first (notebooks, PySpark, Scala). Snowflake is warehouse-native and SQL-first. The 2026 reality is convergence: Databricks ships SQL warehouses, Snowflake ships Iceberg interop and Cortex. The choice usually decides on team skills and existing tool investment.
What is Unity Catalog?
Unity Catalog is Databricks' unified governance layer for data, AI assets (models, features, vector indexes), and access control across the lakehouse. It is the 2026 successor to the older Hive Metastore. Unity Catalog plus Databricks Apps form the access-control and governance backbone of any production Databricks deployment.
How is Databricks licensed?
Per-DBU (Databricks Unit) consumption, with rates varying by compute type (Jobs Compute, All-Purpose Compute, SQL Warehouse, Serverless). DBU rates also vary by cloud provider (AWS, Azure, GCP) and edition (Standard, Premium, Enterprise). Most enterprises land at $400,000 to $5M per year for production Databricks usage.
What is Mosaic AI?
Mosaic AI is Databricks' AI platform, built on the MosaicML acquisition in 2023. It includes model serving, fine-tuning, vector search, agent framework, and the AI Gateway. Positioned against Snowflake Cortex and the major cloud providers' AI services.
Is Databricks an open-source platform?
Partially. Spark, Delta Lake, MLflow, and Unity Catalog (open-sourced in 2024) are open-source projects Databricks contributes to and maintains commercial versions of. The Databricks SaaS platform itself is proprietary, though customers can run open-source components outside the SaaS.
When does Databricks win over a warehouse?
When workloads include significant unstructured data (text, images, audio), when the team is code-first PySpark or Scala, when ML model training and serving live alongside analytics, and when Delta Lake or Iceberg interop matters. Warehouses still win for SQL-only analytical concurrency at large user count.
How does Thinklytics work on Databricks?
We ship Databricks for AI-heavy and unstructured-data workloads, often in parallel with Snowflake or as a Spark-and-ML successor to legacy Hadoop or Synapse stacks. See [Databricks AI consulting](/insights/databricks-ai-consulting-2026) for the engagement scope and [Snowflake vs Databricks AI workloads](/insights/snowflake-vs-databricks-ai-workloads-2026) for the cross-vendor comparison.