Azure Databricks
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Unified Analytics Platform with Azure Databricks
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Single platform for data engineering, data science, machine learning, and analytics workloads with collaborative notebooks and shared compute resources.
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Production-ready AI Gateway for unified LLM endpoint management, cost tracking, rate limiting, and governance across multiple AI providers.
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Instant-on serverless SQL warehouses, notebooks, and JAR job support with automatic scaling, zero infrastructure management, and pay-per-second billing.
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Photon engine delivers up to 12x faster query performance, automatic query optimization, and native integration with Delta Lake for ACID transactions.
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Native Apache Iceberg support with foreign table integration, automatic table maintenance, and seamless migration from external Iceberg catalogs.
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Fine-grained security with attribute-based policies for dynamic data masking, row-level security, and column-level access control across Unity Catalog.
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Open protocol developed by Databricks for secure data sharing with other organizations regardless of the computing platforms they use.
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Real-time feature serving with millisecond latency for production ML applications, automatic feature computation, and versioning.
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Infrastructure-as-code for Databricks assets with version control, automated deployments, and environment promotion capabilities.
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C5 and K-FSI compliance, OAuth token federation, encryption at rest and in transit, private endpoints, and comprehensive audit logging.
Demos, docs and playgrounds
Helpful resources
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Complete Microsoft Learn documentation with quickstarts, tutorials, API references, and architectural guidance.
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Latest platform updates including Mosaic AI Gateway GA, ABAC, serverless JAR jobs, and Iceberg foreign tables.
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Unified LLM management with cost tracking, rate limiting, governance, and multi-provider support now in GA.
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Unified governance for data, ML models, and AI assets with ABAC, data lineage, and audit capabilities.
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Instant-on compute for SQL warehouses, notebooks, and JAR jobs with automatic scaling and optimization.
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ACID transactions, time travel, schema enforcement, and optimized performance for data lakes.
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Managed Iceberg tables with foreign table support for seamless integration with external Iceberg catalogs.
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Infrastructure-as-code for CI/CD workflows with version control and automated deployment capabilities.
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Online and offline feature stores for real-time ML serving with automatic feature computation and versioning.
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Open protocol for secure cross-organization data sharing with streaming tables and change data feed support.
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Enhanced SQL editor with AI-assisted query writing, visual query builder, and advanced formatting.
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Transparent pricing for DBUs across workload types with calculator and cost optimization recommendations.
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End-to-end ML lifecycle management with experiment tracking, model registry, and deployment capabilities.
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Comprehensive security guide including ABAC, OAuth federation, encryption, and compliance certifications.
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Reference architectures for modern analytics, data lakehouse, and AI/ML solutions on Azure.
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Vectorized query engine delivering up to 12x faster performance for SQL and DataFrame operations.
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Complete REST API documentation for programmatic workspace management and automation.
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Free online courses covering data engineering, data science, and ML engineering on Databricks.
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Official GitHub repository with reference implementations, notebooks, and best practice examples.
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Active community forum for troubleshooting, best practices, and connecting with Databricks experts.
