Microsoft Fabric — Technology Profile & Architecture

Core Information

#core_information

Name, description, vendor website, logo, technology type and tags.

Overview & Role

Microsoft Fabric is an all-in-one analytics solution for enterprises that covers everything from data movement to data science, Real-Time Analytics, and business intelligence. It offers a comprehensive suite of services, including Data Factory, Synapse Data Engineering, Synapse Data Warehousing, Synapse Real-Time Analytics, Synapse Data Science, Data Activator, and Power BI, all integrated into a single product. Fabric aims to simplify analytics by providing a unified experience and a single copy of data stored in OneLake, a lake-centric SaaS data platform.

Domain Classification & Tags

Analytics Cloud Multi Model

Performance Profile

#performance_profile

Typical read and write throughput, payload size and processing latency.

Read Performance Profile

Throughput: Varies significantly based on workload and compute SKU (e.g., F2 to F2000+). Can range from hundreds of MB/s to multiple GB/s for large-scale analytics.

Payload Size: Highly variable, from small lookup queries (KB) to large analytical scans (GBs or TBs).

Processing Latency: Typically 100ms to several seconds for interactive queries; minutes for complex analytical jobs.

Write Performance Profile

Throughput: Varies based on data ingestion method (e.g., streaming, batch) and compute SKU. Can range from MB/s to GB/s for high-volume ingestion.

Payload Size: Highly variable, from small event streams (KB) to large batch loads (GBs or TBs).

Processing Latency: Near real-time for streaming ingestion (sub-second to seconds); minutes to hours for large batch loads.

Architecture Diagram

#architecture_diagram

Reference diagram of the technology's internal architecture.

Component Architecture & Topology

open_in_new Standalone Tab

Features

#features

Catalogued product capabilities and what each one does.

Empirical data for features is currently being compiled in the global catalog.

Typical Use Cases

#typical_use_cases

Scenarios the technology is commonly chosen for.

Empirical data for typical use cases is currently being compiled in the global catalog.

Known Customers

#known_customers

Publicly referenced organisations using the technology.

Empirical data for known customers is currently being compiled in the global catalog.

Known Integrations

#known_integrations

Other products and services it is documented to work with.

Empirical data for known integrations is currently being compiled in the global catalog.

Connectors

#connectors

Directional data connections to other technologies, with direction and maturity.

Empirical data for connectors is currently being compiled in the global catalog.

Reference Architectures

#reference_architectures

Published architectures where the technology is used or mentioned.

No published reference architecture blueprints currently link to Microsoft Fabric.

Security Features

#security_features

Built-in security and access-control capabilities.

Empirical data for security features is currently being compiled in the global catalog.

Known Issues

#known_issues

Documented limitations, defects and operational pitfalls.

Empirical data for known issues is currently being compiled in the global catalog.

Guidelines

#guidelines

Recommended practices for adopting and operating the technology.

Empirical data for guidelines is currently being compiled in the global catalog.

Standards & Compliance

#standards_and_compliance

Standards, certifications and control requirements it maps to.

Empirical data for standards & compliance is currently being compiled in the global catalog.

Sources

#sources

Documentation and research references behind the recorded information.

Empirical data for sources is currently being compiled in the global catalog.

Expert Validation

#expert_validation

Whether domain experts reviewed and confirmed the content.

Empirical data for expert validation is currently being compiled in the global catalog.