π Azure Synapse Analytics Architecture Diagrams¶
π Home > π Diagrams
π¨ Visual Architecture Gallery
This section contains comprehensive architecture diagrams for Azure Synapse Analytics components and workflows, focusing on Delta Lakehouse and Serverless SQL capabilities.
ποΈ Delta Lakehouse Architecture¶
πΌοΈ Architecture Overview¶
π‘ Architecture Insight
The diagram above shows the logical architecture of a Delta Lakehouse implementation in Azure Synapse Analytics, highlighting the unified approach to batch and real-time analytics.
π Key Components¶
| Component | Role | Key Features | Integration Level |
|---|---|---|---|
| ποΈ Azure Data Lake Storage Gen2 | Foundation storage layer | Hierarchical namespace, security, scalability | |
| π₯ Azure Synapse Spark Pools | Distributed compute engine | Auto-scaling, multiple languages, ML support | |
| ποΈ Delta Lake | Storage format and engine | ACID transactions, time travel, schema evolution | |
| π Azure Synapse Pipeline | Data orchestration | ETL/ELT workflows, scheduling, monitoring | |
| βοΈ Azure Synapse Serverless SQL | Query interface | Pay-per-query, T-SQL compatibility |
βοΈ Serverless SQL Architecture¶
πΌοΈ Query Architecture¶
π° Cost-Effective Querying
The diagram illustrates the serverless SQL query architecture in Azure Synapse Analytics, showcasing the pay-per-query model and distributed processing capabilities.
βοΈ Architecture Components¶
| Component | Function | Supported Formats | Performance |
|---|---|---|---|
| βοΈ Serverless SQL Pool | On-demand query processing | T-SQL compatible | |
| ποΈ Storage Layer | Data lake and blob storage | ADLS Gen2, Blob, external sources | |
| π File Formats | Multiple format support | Parquet, Delta, CSV, JSON, ORC | |
| βοΈ Query Engine | Distributed processing | Parallel execution, optimization | |
| π Result Delivery | Multiple output options | JDBC/ODBC, export, caching |
π Shared Metadata Architecture¶
πΌοΈ Unified Metadata¶
π Cross-Engine Compatibility
The diagram demonstrates how metadata can be shared across different compute engines in Azure Synapse Analytics, enabling seamless cross-engine data access.
π Metadata Components¶
| Component | Purpose | Engine Compatibility | Metadata Scope |
|---|---|---|---|
| π Synapse Workspace | Central management hub | All engines | |
| πΊοΈ Metadata Services | Unified metadata layer | Cross-engine sharing | |
| π₯ Spark Metastore | Hive-compatible catalog | Spark, external tools | |
| π SQL Metadata | Relational catalog | SQL pools, serverless | |
| π Integration Runtime | Data movement metadata | Pipelines, external systems |
Data Flow Diagrams¶
Delta Lake Write Flow¶
ββββββββββββββ ββββββββββββββ ββββββββββββββ ββββββββββββββ
β Raw Data ββββββΆβ Spark Pool ββββββΆβ Processing ββββββΆβ Delta Lake β
ββββββββββββββ ββββββββββββββ ββββββββββββββ ββββββββββββββ
β
βΌ
ββββββββββββββ
β Metadata β
β Update β
ββββββββββββββ
Serverless SQL Query Flow¶
ββββββββββββββ ββββββββββββββ ββββββββββββββ ββββββββββββββ
β User ββββββΆβ SQL Query ββββββΆβ Query Plan ββββββΆβ Query β
β Query β β Parser β β Generation β β Execution β
ββββββββββββββ ββββββββββββββ ββββββββββββββ ββββββββββββββ
β
βΌ
ββββββββββββββ ββββββββββββββ ββββββββββββββ
β Results βββββββ Result βββββββββββββββββββββββββ Data Sourceβ
β β β Processing β β Access β
ββββββββββββββ ββββββββββββββ ββββββββββββββ
π¨ Creating Architecture Diagrams¶
π οΈ Diagramming Toolkit
Professional diagram creation requires the right tools and standards.
π» Recommended Diagramming Tools¶
| Tool | Type | Best For | Skill Level |
|---|---|---|---|
| π Microsoft Visio | Professional software | Enterprise architecture, detailed technical diagrams | |
| π Draw.io | Web-based, free | Quick diagrams, collaboration, Azure stencils | |
| π Lucidchart | Cloud-based | Team collaboration, real-time editing | |
| π Mermaid | Code-based | Documentation integration, version control | |
| π¨ Azure Architecture Center | Templates | Azure-specific patterns, best practices |
π Diagram Standards and Guidelines¶
π¨ Visual Excellence
Consistent, professional diagrams enhance understanding and maintain documentation quality.
π Quality Standards¶
| Standard | Requirement | Purpose | Impact |
|---|---|---|---|
| π’ Azure Official Icons | Use only Microsoft-provided icons | Brand consistency, recognition | |
| π¨ Consistent Colors | Standardized color palette | Visual harmony, readability | |
| π·οΈ Clear Labels | All components labeled | Understanding, accessibility | |
| πΊοΈ Legend Inclusion | Legend for complex diagrams | Clarity, reference | |
| π· High Resolution | Minimum 300 DPI for print | Professional quality, scalability | |
| πΌοΈ PNG Format | Transparent backgrounds preferred | Web compatibility, flexibility | |
| π Multiple Views | Logical and physical perspectives | Comprehensive understanding |
π¨ Azure Color Palette¶
| Service Category | Primary Color | Secondary Color | Usage |
|---|---|---|---|
| π Analytics | Synapse, Data Factory | ||
| ποΈ Storage | ADLS, Blob Storage | ||
| π Security | Key Vault, Security Center | ||
| π Networking | VNet, Load Balancer |
β οΈ Implementation Status¶
π§ Work in Progress
This diagram gallery is currently under development with professional visual assets.
π Diagram Development Roadmap¶
| Diagram Type | Status | Priority | Completion Target |
|---|---|---|---|
| ποΈ Delta Lakehouse | Q1 2025 | ||
| βοΈ Serverless SQL | Q1 2025 | ||
| π Shared Metadata | Q2 2025 | ||
| π Data Flow | Q2 2025 |
π Contribution Welcome
The text-based diagrams serve as placeholders for professional visual diagrams that should follow the standards outlined above. Community contributions of high-quality diagrams are welcome!
π Specialized Diagram Collections¶
π Extended Visual Resources
Explore specialized diagram collections for specific architectural domains.
π Collection Categories¶
| Collection | Focus Area | Diagram Count | Complexity Level |
|---|---|---|---|
| π Data Governance | Governance workflows, lineage, compliance | ||
| π Security Architecture | Security controls, network isolation, threat models | ||
| π Process Flowcharts | Operational workflows, decision trees, procedures |
π Visual Learning Architecture diagrams are essential for understanding complex systems. Use these visual resources to enhance your Azure Synapse Analytics knowledge and share architectural concepts with your team.
π Get Started Begin with the Delta Lakehouse overview to understand the foundational concepts, then explore the corresponding architectural diagrams.