Databricks Data + AI Platform
Product · SaaS / cloud software · Data & analytics by Databricks
Unify your data, analytics and AI on one open platform.
The Databricks Data + AI Platform is a unified cloud-based environment for data engineering, data science, and machine learning. It is designed for businesses to manage and analyze large volumes of data efficiently by unifying data silos into a single collaborative workspace built on Apache Spark. The platform enables teams to clean and process data, build and train AI models, and deploy analytics at scale on an open lakehouse architecture. It supports multi-cloud deployments across AWS, Microsoft Azure, and Google Cloud, providing built-in governance through Unity Catalog.
- Languages
- English
- Underlying Engine
- Apache Spark
- Architecture
- Lakehouse
- Cloud Providers
- AWS, Azure, Google Cloud
- Governance Layer
- Unity Catalog
Overview
The Databricks Data + AI Platform is a unified cloud-based environment for data engineering, data science, and machine learning. It is designed for businesses to manage and analyze large volumes of data efficiently by unifying data silos into a single collaborative workspace built on Apache Spark. The platform enables teams to clean and process data, build and train AI models, and deploy analytics at scale on an open lakehouse architecture. It supports multi-cloud deployments across AWS, Microsoft Azure, and Google Cloud, providing built-in governance through Unity Catalog.
Core Platform Capabilities
- Serverless Data Warehousing: A serverless data warehouse built on lakehouse architecture that offers high price-performance for analytics workloads.
- Unity Catalog Integration: Unified governance for data and AI assets, including access control, discovery, and lineage tracking.
- AI/BI Integration: Natively integrated AI-powered business intelligence for creating dashboards and visualizations.
- Collaborative Workspace: A collaborative environment for data engineering, data science, and machine learning built on Apache Spark.
Data Engineering and Sharing
- Lakeflow: Automate data ingestion and orchestration for reliable analytics and AI pipelines.
- Databricks Apps: Build and deploy secure data and AI applications using serverless compute and built-in governance.
- Delta Sharing: Securely share data and AI assets across organizations and platforms without brittle pipelines.
Specifications
- Underlying Engine
- Apache Spark
- Architecture
- Lakehouse
- Cloud Providers
- AWS, Azure, Google Cloud
- Governance Layer
- Unity Catalog
Added by AntSpace from public sources (databricks.com).